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Abstract This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of “big data” (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA’s activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors.
Subcortical abnormalities in schizophrenia, bipolar disorder, major depressive disorder, and ADHD. a ENIGMA's publications of the three largest neuroimaging papers on schizophrenia (SCZ), bipolar disorder (BD), and major depressive disorder (MDD), suggested widespread cross-disorder differences in effects (van Erp et al. 54 , Hibar et al. 68 ). By processing 21,199 people's brain MRI scans consistently, we found greater brain structural abnormalities in SCZ and BD versus MDD, and a very different pattern in attention-deficit/hyperactivity disorder (ADHD; Hoogman et al. 7 ). Subcortically, all three disorders involve hippocampal volume deficits -greatest in SCZ, least in MDD, and intermediate in BD. As a slightly simplified 'rule of thumb', the hippocampus, ventricles, thalamus, amygdala and nucleus accumbens show volume reductions in MDD that are around half the magnitude of those seen in BD, which in turn are about half the magnitude of those seen in SCZ. The basal ganglia are an exception to this rule-perhaps because some antipsychotic treatments have hypertrophic effects on the basal ganglia, leading to volume excesses in medicated patients. In ADHD, however, the amygdala, caudate and putamen, and nucleus accumbens all show deficits, as does ICV (ventricular data is not included here for ADHD, as it was not measured in the ADHD study). A web portal, the ENIGMA Viewer, provides access to these summary statistics from ENIGMA's published studies of psychiatric and neurological disorders (http:// enigma-viewer.org/About_the_projects.html). b Independent work by the Japanese Consortium, COCORO, found a very similar set of effect sizes for group differences in subcortical volumes between schizophrenia patients and matched controls.
… 
White matter microstructure in schizophrenia, major depressive disorder, and 22q11.2 deletion syndrome. a White matter microstructural abnormalities are shown, by tract, based on the largest-ever diffusion MRI studies of these three disorders. In schizophrenia (SCZ), fractional anisotropy, a measure of white matter microstructure, is lower in almost all individual regions, and in the full skeleton. In major depressive disorder (MDD), a weak pattern of effects is observed, again with MDD patients showing on average lower FA across the full white matter skeleton, when compared to controls. In comparisons between 22q11.2 deletion syndrome (22q11DS) and matched controls, by contrast, the average FA along the full white matter skeleton does not show systematic differences; instead, while some regions do show on average lower FA in affected individuals compared with controls, several white matter regions show higher FA. b Relative to appropriately matched groups of healthy controls (HC), group differences in fractional anisotropy are shown for ENIGMA's studies of SCZ, MDD (both in adults), and 22q11.2 deletion syndrome. [Data adapted, with permission of the authors and publishers, from Kelly et al. 56 , van Velzen et al. 67 , and Villalón-Reina et al. 17 ; a key to the tract names appears in the original papers; some tracts (i.e. the hippocampal portion of the cingulum) were omitted from the 22q11DS analysis as they were not consistently in the field of view for some cohorts of the working group].
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Thompson et al. Translational Psychiatry (2020) 10:100
https://doi.org/10.1038/s41398-020-0705-1
T
ranslational Psychiatry
REVIEW ARTICLE Open Access
ENIGMA and global neuroscience: A decade
of large-scale studies of the brain in health
and disease across more than 40 countries
Abstract
This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta
Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health
and disease. Building on large-scale genetic studies that discovered the rst robustly replicated genetic loci associated
with brain metrics, ENIGMA has diversied into over 50 working groups (WGs), pooling worldwide data and expertise
to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on
specic psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences,
or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized
analyses of big data(i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These
international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major
depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-
decit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent
ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating
disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here,
we summarize the rst decade of ENIGMAs activities and ongoing projects, and describe the successes and challenges
encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for
testing reproducibility and robustness of ndings, offering the opportunity to identify brain systems involved in clinical
syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial
factors.
Introduction
The ENIGMA (Enhancing NeuroImaging Genetics
through Meta Analysis) Consortium is a collaboration of
more than 1400 scientists from 43 countries studying the
human brain. ENIGMA started 10 years ago, in 2009, with
the initial aim of performing a large-scale neuroimaging
genetic study, and has since diversied into 50 working
groups (WGs), pooling worldwide data, resources and
expertise to answer fundamental questions in neu-
roscience, psychiatry, neurology, and genetics (Fig. 1
shows a world map of participating sites, broken down by
working group). Thirty of the ENIGMA WGs focus on
specic psychiatric and neurologic conditions. Four study
different aspects of development and aging. Others study
key transdiagnostic constructs, such as irritability, and the
importance of evolutionarily interesting genomic regions
in shaping human brain structure and function. Central to
the success of these WGs are the efforts of dedicated
methods development groups within ENIGMA. There are
currently 12 WGs that develop and disseminate multi-
scale and big dataanalysis pipelines to facilitate harmo-
nized analyses using genetic and epigenetic data,
multimodal (anatomical, diffusion, functional) magnetic
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Correspondence: Paul M. Thompson (pthomp@usc.edu)
Full list of author information is available at the end of the article.
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resonance imaging (MRI) and spectroscopy (MRS) mea-
sures, in combination with genetic and epigenetic data,
and data from electroencephalography (EEG).
The Consortium has been a formidable force for dis-
covery and innovation in human brain imaging, sup-
porting more than 200 active studies. The disorder-
specic WGs have published the largest neuroimaging
studies to date in schizophrenia (SCZ; total N=9572;
4474 cases)
1
, bipolar disorder (BD; total N=6503; 2447
cases)
2
, major depressive disorder (MDD; total N=
10,105; 2148 cases)
3
, post-traumatic stress disorder
(PTSD; total N=1868; 794 cases)
4
, substance use dis-
orders (SUD; total N=3240; 2140 cases)
5
, obsessive-
compulsive disorder (OCD; total N=3665; 1905 cases)
6
,
attention-decit/hyperactivity disorder (ADHD; total N=
4180; 2246 cases)
7
, autism spectrum disorders (ASD; total
N=3222; 1571 cases)
8
, epilepsy (N=total 3876; 2149
cases)
9
, and 22q11.2 deletion syndrome (22q11DS; total
N=944; 474 cases)
10
. Key results of these studies are
summarized in Table 1. Building on this work, the focus
of the ENIGMA disorder-specic WGs now goes beyond
traditional diagnostic boundaries. As these rst large-scale
studies are being completed, ENIGMA is beginning to
identify shared and distinct neuroimaging patterns in
brain disorders with known genetic or clinical over-
lap
11,12
, and to delineate the role of transdiagnostic risk
factors (e.g., childhood trauma) and clinical phenomena
(e.g., suicidal thoughts and behaviors). In addition,
ENIGMAs genetic studies are now analyzing imaging and
genetics data from more than 50,000 people to uncover
genetic markers that most robustly associated with brain
structure and function, or imaging derived neurobiologi-
cal traits related to various disease conditions
1316
.
As we detail in this review, the ENIGMA Consortium
has made multiple, seminal contributions to neuroscience
and psychiatry, including (a) characterization of robust
neuroimaging proles for various brain disorders, (b)
standardization of metrics used to assess clinical symp-
toms of patients across multiple research sites, and (c) use
of dimensional approaches that go beyond the
casecontrol comparisons of individuals with categorical
diagnoses, and further enable the investigation of specic
genetic, and environmental features or neurobiological
markers associated with disorder risk and treatment
Fig. 1 World Map of ENIGMAs Working Groups. The ENIGMA Consortium has grown to include over 1400 participating scientists from over 200
institutions, across 43 countries worldwide. ENIGMA is organized as a set of 50 WGs, studying 26 major brain diseases (see color key). Each group
works closely with the others and consists of worldwide teams of experts in each brain disorder as well as experts in the major methods used to
study each disorder. The diseases studied include major depressive disorder, bipolar disorder, schizophrenia, substance use disorder, post-traumatic
stress disorder, attention-decit/hyperactivity disorder, obsessive-compulsive disorder, and autism spectrum disorder, and several neurological
disorders, including Parkinsons disease, epilepsy, ataxia, and stroke. In recent years, new WGs were created that grew into worldwide consortia on
epilepsy (Whelan et al.
9
), eating disorders (King et al.
104
), anxiety disorders (Groenewold et al.
107
), antisocial behavior, and infant neuroimaging.
Thompson et al. Translational Psychiatry (2020) 10:100 Page 2 of 28
Table 1 A Selection of key ndings from ENIGMAs Working Groups, along with key papers and current sample sizes.
Working
group
Number of
datasets
Total N
(patient N)
Age range
(in years)
Relevant publications Main ndings
Clinical
22Q11DS 14 863 (533) 656 Villalón-Reina et al.
17
; Sun et al.
10
Widespread reductions in diffusivity,
pronounced in regions with major cortico-
cortical and cortico-thalamic bers; thicker
cortical gray matter overall, but focal thickness
reduction in temporal and cingulate cortex;
cortical surface area showed pervasive
reductions; lower cortical surface area in
individuals with larger microdeletion; 22q-
related psychosis associated with lower
cortical thickness and signicantly overlapped
with ndings from ENIGMA-SCZ group.
Addiction/
SUDs
118 18,823 (6,592) 768 Mackey et al.
5,84
; Conrod et al.
86
Common neural substrate shared in
dependence; differential patterns of regional
volume as biomarkers of dependence on
alcohol and nicotine; lower volume or
thickness observed, with greatest effects
associated with alcohol use disorder; insula
and medial orbitofrontal cortex affected,
regardless of dependence.
ADHD 37 4180 (2246) 463 Hoogman et al.
7,91
; Klein et al.
47
;
Zhang-James
94
; Hess et al.
92
Reduction in bilateral amygdala, striatal, and
hippocampal volumes in the ADHD
population, especially in children; lower
cortical surface area values found in children
with ADHD, but not in adolescents or adults;
lower surface area associated with ADHD
symptoms in the general population in
childhood; genetic association studies suggest
that genes involved in neurite outgrowth play
a role in ndings of reduced volume in ADHD;
gene-expression studies imply that structural
brain alterations in ADHD can also be
explained in part by the differential
vulnerability of these regions to mechanisms
mediating apoptosis, oxidative stress, and
autophagy.
ASD 54 3583 (1774) 264 Postema et al.
97
; van Rooij et al.
8
Altered morphometry in the cognitive and
affective parts of the striatum, frontal cortex
and temporal cortex in ASD.
BD 44 11,100 (3100) 886 Favre et al.
69
; Nunes et al.
23
;
Hibar et al.
2,68
Volumetric reductions in hippocampus and
thalamus and enlarged lateral ventricles in
patients; thinner cortical gray matter in
bilateral frontal, temporal and parietal regions;
strongest effects on left pars opercularis,
fusiform gyrus and rostral middle frontal
cortex in BD.
Thompson et al. Translational Psychiatry (2020) 10:100 Page 3 of 28
Table 1 continued
Working
group
Number of
datasets
Total N
(patient N)
Age range
(in years)
Relevant publications Main ndings
Eating
Disorders
28 anorexia
nervosa (AN);
12 bulimia
nervosa (BN)
2531 (897 AN;
307 BN)
1050 AN;
1246 BN
Walton et al.
48
Signs of inverse concordance between greater
thalamus volume and risk for anorexia nervosa
(AN); variation in gene DRD2 signicantly
associated with AN only after conditioning on
its association with caudate volume; genetic
variant linked to LRRC4C reached signicance
after conditioning on hippocampal volume.
Epilepsy 24 3876 (2149) 1855 Whelan et al.
9
Patients with IGE showed volume reductions
in the right thalamus and lower thickness in
the bilateral precentral gyri; both MTLE
subgroups showed volume reductions in the
ipsilateral hippocampus, and lower thickness
in extrahippocampal cortical regions,
including the precentral and paracentral gyri;
lower subcortical volume and cortical
thickness were associated with a longer
duration of epilepsy in the all-epilepsies and
right MTLE groups.
HIV 12 1044 (all
patients)
2281 Nir et al.
124,169,170
; Fouche et al.
171
In the full group, subcortical volume
associations implicated the limbic system:
lower current CD4+counts were associated
with smaller hippocampal and thalamic
volumes; a detectable viral load was
associated with smaller hippocampal and
amygdala volumes; limbic effects were largely
driven by participants on cART; in subset of
participants not on cART, smaller putamen
volumes were associated with lower CD4+
count.
MDD 38 14,249 (4379) 1089 van Velzen et al.
67
; Tozzi et al.
75
; Han
et al.
72
; Frodl et al.
74
; Renteria et al.
172
;
Schmaal et al.
3,70
; Ho et al.
137
;
Saemann et al.
83
Signicantly lower hippocampal volumes;
thinner orbitofrontal cortex, anterior and
posterior cingulate, insula and temporal lobes
cortex in adult MDD patients; lower total
surface area and regional reductions in frontal
regions and primary and higher-order visual,
somatosensory and motor areas in
adoloescent MDD patients; greater exposure
to childhood adversity associated with smaller
caudate volumes in females, independent of
MDD; patients reporting suicidal plans or
attempts showed a smaller ICV volume
compared to controls.
OCD 38 3665 (1905) 565 Boedhoe et al.
6,88,167
; Hibar et al.
45
Subcortical abnormalities in pediatric and
adult patients; pallidum (bigger) and
hippocampus (smaller) key in adults, and
thalamus (bigger) key in (unmedicated)
pediatric group; parietal cortex consistently
Thompson et al. Translational Psychiatry (2020) 10:100 Page 4 of 28
Table 1 continued
Working
group
Number of
datasets
Total N
(patient N)
Age range
(in years)
Relevant publications Main ndings
implicated both in children and adults; more
widespread cortical thickness abnormalities in
medicated adults, and more pronounced
surface area decits (mainly in frontal regions)
in medicated pediatric OCD patients.
PTSD 16 3118 (1288) 1785 Dennis et al.
76
; Salminen et al.
80
;
Logue et al.
4
;OLeary et al.
78
Signicantly smaller hippocampi, on average,
in individuals with current PTSD compared
with trauma-exposed control subjects, and
smaller amygdalae.
Schizophrenia 39 9572 (4474) 1877 Holleran et al.
57
; van Erp et al.
1,54,55
;
Kelly et al.
56
; Walton et al.
62,63
;
Kochunov et al.
66
Positive symptom severity was negatively
related to bilateral STG thickness; widespread
thinner cortex and smaller surface area, largest
effect sizes in frontal and temporal lobe
regions; smaller hippocampus, amygdala,
thalamus, accumbens and intracranial
volumes; larger pallidum and lateral ventricle
volumes; widespread reductions in FA, esp. in
anterior corona radiata and corpus callosum;
higher mean and radial diffusivity; left MOFC
thickness signicantly associated with
negative symptom severity; link between
prefrontal thinning and negative symptom
severity in schizophrenia.
CNV 37 16,889 (24
16p11.2 distal
and 125 15q11.2
CNV carriers)
390 van der Meer et al.
100
; Sonderby
53
16p11.2 distal CNV: Negative dose-response
associations with copy number on intracranial
volume and regional caudate, pallidum and
putamen volumes. 15q11.2 CNV: Decrease in
accumbens and cortical surface area in
deletion carriers and negative dose response
on cortical thickness.
Non-clinical
EEG 5 8425 573 Smit et al.
40
Identied several novel genetic variants
associated with oscillatory brain activity;
replicated and advanced understanding of
previously known genes associated with
psychopathology (i.e., schizophrenia and
alcohol use disorders); these
psychopathological liability genes affect brain
functioning, linking the genesexpression to
specic cortical/subcortical brain regions.
GWAS 34 22,456 391 Satizabal et al.
14
; Grasby et al.
13
;
Hibar et al.
25,173
; Adams et al.
169
Over 200 genetic loci where common
variation is associated with cortical thickness
or surface area; over 40 common genetic
variants associated with subcortical volumes.
Laterality 99 17,141 390 de Kovel et al.
71
; Kong et al.
90,154
;
Postema et al.
97
; Guadalupe et al.
174
Average patterns of left-right anatomical
asymmetry of the healthy brain were mapped,
Thompson et al. Translational Psychiatry (2020) 10:100 Page 5 of 28
outcome. The large scale and inclusivity of these analyses
in terms of populations, sample sizes, numbers of
coordinating centers, and diversity of imaging and genetic
datahas been instrumental for demonstrating robust
associations between clinical factors and brain alterations,
and for stratifying patients with the same diagnosis
according to differential treatment outcomes
10,17
. Thus, a
valuable aspect of the existing ENIGMA studies is the
ability to identify the most robust pattern of non-
invasively measured neurobiological features involved in
clinical syndromes across multiple samples that are more
representative of the global population. This also results
in robust effect size estimates, without the confounds of
literature-based meta-analyses based on published data
with possible publication bias (as noted in Kong et al.)
18
.
These data also provide a unique opportunity to assess
Table 1 continued
Working
group
Number of
datasets
Total N
(patient N)
Age range
(in years)
Relevant publications Main ndings
as regards cortical regional surface areas,
thicknesses, and subcortical volumes; fronto-
occipital gradient in cortical thickness
asymmetry was found, with frontal regions
generally thicker on the left, and occipital
regions on the right; asymmetries of various
structural measures were signicantly
heritable, indicating genetic effects that differ
between the two sides; age, sex and
intracranial volume affected some
asymmetries, but handedness did not;
disorder casecontrol analyses revealed subtle
reductions of regional cortical thickness
asymmetries in ASD, as well as altered
orbitofrontal surface area asymmetry; little
evidence for altered anatomical asymmetry
was found in MDD; pediatric patients with
OCD showed evidence for altered asymmetry
of the thalamus and pallidum.
Lifespan 91 14,904 healthy
individuals
292 Dima et al.
175
; Frangou et al.
176
Thickness in almost all cortical regions
decreased prominently in the rst two to three
decades of life, with an attenuated or
plateaued slope afterwards; exceptions to this
pattern were entorhinal and temporopolar
cortices whose thickness showed an
attenuated inverse U-shaped relation with age,
and anterior cingulate cortex, which showed a
U-shaped association with age; age at peak
cortical thickness was 67 years for most brain
regions.
Plasticity 36 10,199 (2242) 697 Brouwer et al.
38,39
Heritability estimates of change rates were
generally higher in adults than in children
suggesting an increasing inuence of genetic
factors explaining individual differences in
brain structural changes with age; for some
structures, the genetic factors inuencing
change were different from those inuencing
the volume itself, suggesting the existence of
genetic variants specic for brain plasticity.
Thompson et al. Translational Psychiatry (2020) 10:100 Page 6 of 28
important sources of disease heterogeneity, including key
genetic, environmental, demographic, and psychosocial
factors. Here, we provide a synopsis of the rst decade of
ENIGMAs activities and highlight the successes and
challenges encountered along the way.
History
ENIGMA was launched in December 2009 to help
break the logjamin genetic studies of the brain. At the
time, most neuroimaging genetics studies were assessing
historically candidate genetic variations, mostly in very
small samples of a few tens to hundreds of participants
(e.g., COMT,5-HTTLPR, BDNF). These studies typically
reported candidate geneeffects that did not replicate
when tested in independent cohorts
1921
. It became
apparent that very large numbers of genetic loci con-
tributed to variation in complex neurological or psychia-
tric traits, including imaging-derived brain measures
each with a very small effect sizeand only a few genetic
loci accounted for more than 1% of the variance in any
complex brain condition or measure
22
. Thus, scientists
began to recognize the need to pool multiple datasets
worldwide to perform better-powered studies of these
traits. In response, the ENIGMA Consortiums initial plan
was to merge two big datasourcesneuroimaging and
geneticswith the aim of discovering the impact of
genetic factors on brain systems, to determine whether
these genetic factors underlie manifestation of disorders
within the brain, and to identify diagnostic and prognostic
neuroimaging biomarkers. A further goal was to improve
on previous literature-based meta-analyses by using har-
monized processing and analysis protocols on an unpre-
cedented scale. This was the impetus that launched
ENIGMAs early studies.
In 2014, the NIH Big Data to Knowledge (BD2K) pro-
gram awarded a consortium grant to ENIGMA with seed
funding for WGs on nine disorders: SCZ, BD, MDD,
OCD, ADHD, ASD, SUD, 22q11DS, and the effects of the
human immunodeciency virus (HIV) on the brain. This
support led to the largest neuroimaging studies for the
nine targeted disorders, with results reported in over 50
manuscripts. These initial successes provided the driving
force to establish an additional 21 disease WGs (see
Working Group chart, Fig. 2).
Following the model established by the Psychiatric
Genomics Consortium (PGC), which emphasized har-
monization of genomic analysis protocols across sites, the
ENIGMA Consortium created harmonized protocols to
analyze brain structure and function, along with genetic,
and clinical data across its WGs. Instead of centralizing
data, ENIGMA opted to work as a distributed con-
sortium, asking groups to run standardized protocols
themselves, rather than the approach used in the PGC,
where data are centralized. At the time, ENIGMA design
was important for the rapid acceptance of the consortium
in the eld, as it made contribution very easy; further, the
memoranda of understanding provided the basic
Fig. 2 ENIGMAs Working Group Flowchart. ENIGMAs working
groups are divided into technical groups that work on testing
harmonized methods, and clinical groups that study different
disorders and conditions across psychiatry and neurology, as well as
some behaviors (e.g., schizotypy and antisocial behaviors). The use of
harmonized analysis methods across all the working groups has
enabled cross-disorder comparisons (e.g., in the affective/psychosis
spectrum of depression to bipolar disorder to schizophrenia), and
transdiagnostic analyses of risk factors such as childhood trauma
across a number of disorders (such as major depressive disorder
(MDD) and post-traumatic stress disorder (PTSD)). Several working
groups, such as brain trauma and anxiety, consist of several subgroups
examining subtypes (e.g., panic disorder or social anxiety), and allow
analyses of overlap and differences (e.g., between military and civilian
brain trauma).
Thompson et al. Translational Psychiatry (2020) 10:100 Page 7 of 28
guidelines for the trusted collaborative networks to
develop. In the meantimewith views on data sharing
having changed quite considerablymany ENIGMA
WGs now also share (derived) individual data, allowing
for more in-depth analyses.
In ENIGMAs genetic studies, many participating cen-
ters use different genotyping chips, so data were rst
imputed to common genomic references (such as the
1000 Genomes reference panel), allowing each partici-
pating site to perform the same association tests between
brain measures and genetic variation at over 10 million
loci across the genome. Furthermore, the ENIGMA
Consortium standardized procedures for the extraction
of brain metrics (such as cortical thickness, cortical sur-
face area, and subcortical volume) from raw neuroimaging
data, implemented consensus protocols for data quality
control and outlier handling, and pioneered new
meta-analytic methods for the analysis of aggregated sta-
tistical information (http://enigma.ini.usc.edu/protocols/).
ENIGMAs meta-analyses estimated the size and precision
of the effects after pooling evidence from multiple cohorts,
and they also ranked the neuroimaging effect sizes of
ndings emerging from casecontrol comparisons,
thereby setting the stage for deeper, secondary analyses
aiming to explore potential moderators of psychiatric and
neurological disease. More recently, many ENIGMA
groups have moved beyond cohort level meta-analyses to
pooled, or mega-analyses (Using brain volumetric data
from ENIGMAs OCD, ADHD, and ASD working groups,
Boedhoe et al.
12
compared meta-analysis to mega-analyses
that model site or cohort effects as random effects,
showing broad agreement. Mega-analyses allow more
sophisticated statistical adjustments as they pool more
information across cohorts; meta-analyses tend to be more
efcient when ethical, legal or logistic constraints govern
or restrict individual-level data transfer (e.g., genome-wide
genetic data).), where anonymized and unidentiable
individual-level data are aggregated in a central location,
allowing more exible statistical designs, such as machine
learning analyses
23
, reliable estimation of interaction
effects, and examination of polygenic risk scores. The type
and amount of data transferred for each analysis is chosen
pragmatically for each study. Distributed analyses promote
scientic engagement from many groups worldwide and
take advantage of distributed computing resources that
scale up as the network grows; here the data transferred is
mainly aggregate measures such as quality control metrics
and the statistical metrics derived from agreed-upon
analytical tests. On the other hand, the centralized ana-
lyses are preferable when a variable of interest is sparsely
distributed across sites, (e.g., individuals with 22q11DS
exhibiting psychotic symptoms) or when a specic method
is being developed, and computational power or expertise
is available at only a few sites; here the data transferred
usually include unidentiable derived imaging metrics
(e.g., hippocampal volume) and demographic or clinical
information (age at scan, sex, diagnostic status, etc.);
however, this form of analysis may limit participation and
requires individual data transfer agreements with partici-
pating sites. We note, because of these required agree-
ments with potentially clinically sensitive patient
information, and the project-specic design of the cen-
tralizedapproaches, ENIGMA does not curate a database
for repeated or open access, and each cohort PI approves
of each project for which they contribute data.
ENIGMAs genetic studies
Uncovering the genetic basis of brain morphometric
variation
The rst demonstration of the value of the ENIGMA
approach was the identication of genetic loci associated
with variation in subcortical volumes including the cau-
date, putamen, and hippocampus (see Fig. 3)
14,24,25
. These
genome-wide association studies (GWAS) yielded intri-
guing new leads regarding the genetic architecture of the
human brain that were only possible because ENIGMA
afforded increased power to detect subtle effects. More
recently, ENIGMA identied more than 200 individual
loci that signicantly contribute to variation in brain
measures, with p-values reaching 10
180
; each single locus
accounted for only 0.11% of phenotypic variance, but up
to 20% of the variance in aggregate. For this effort
ENIGMA had partnered with the CHARGE Consortium
and UK Biobank on a series of studies of 70 cortical
measures, including regional cortical thickness and sur-
face area
13
. These discoveries resulted in an annotated
atlas of common genetic variants that contribute to
shaping the human cerebral cortex. Of particular interest,
we found that genetic loci affecting brain morphology
show enrichment for developmentally regulated genes
13
and human-specic regulatory elements
26,27
. Ongoing
efforts are beginning to map these genetic effects at a
ner-grained spatial resolution using shape analysis, sur-
face- and voxel-based analyses
2831
. Moving beyond the
mass univariate methods, which analyze each brain
measure separately, ENIGMA has begun to use multi-
variate methods to meet the challenge of quantifying the
complex relationships between brain networksor con-
nectomes’—and the genome
3234
.
Current ENIGMA sample sizes (which now exceed
50,000) are sufciently large to identify genetic associa-
tions at a pace comparable to that of GWAS for other
phenotypes. In a recent analysis, Holland
35
contrasted
rates of discovery of genetic loci by ENIGMA and the
PGC and noted the distribution of effect sizes for some
brain measures (e.g., putamen volume) may indeed be
enriched for slightly larger effects compared to behavioral
traits (see also Le and Stein
36
and Franke et al.
37
). Still, a
Thompson et al. Translational Psychiatry (2020) 10:100 Page 8 of 28
central understanding gained from the ENIGMA asso-
ciation screens is that neuroimaging genetics studiesjust
like analyses of behavioral measures, require tens (perhaps
hundreds) of thousands of participants to obtain robust
and reproducible effects of common polymorphisms.
Most individual effect sizes are very small explaining
<0.2% of variance, as for other complex human traits.
GWAS of multiple imaging measures may offer a way to
parcellate the brain into clusters or sectors with
overlapping genetic drivers, perhaps boosting the power
to discover genetic loci, by aggregating regions based on
their genetic correlation.
Uncovering the genetic basis of brain change
The quest to discover genetic loci that modulate brain
development and aging led to the launch of the ENIGMA-
Plasticity WG
38
, which uses longitudinal brain imaging
data from 36 cohorts worldwide to estimate rates of brain
Fig. 3 Genetic Inuences on brain structure: effects of common and rare genetic variants. ENIGMAs large-scale genetic analyses study the
effects of both common and rare genetic variants on brain measures. aA series of progressively larger genome-wide association studies have
revealed over 45 genetic loci associated with subcortical structure volumes (Hibar et al.
25
, Satizabal et al.
14
) and over 200 genetic loci associated with
cortical thickness and surface area Grasby et al.
13
. The Manhattan plots here (adapted from Hibar et al.
25
, show the genome (on the x-axis) and the
evidence for association (as a logarithm of the p-value, on the y-axis) for each common genetic variant (or SNP) with the volume of each brain
structure shown. bGenetics of Hippocampal Volume. A subsequent genome-wide association study (GWAS) of 33,536 individuals discovered six
independent loci signicantly associated with hippocampal volume, four of them novel. Of the novel loci, two lie within key genes involved in
neuronal migration and microtubule assembly (ASTN2 and MAST4) (Hibar et al.
173
). An interactive browser, ENIGMA-Vishttp://enigma-brain.org/
enigmaviscan be used to navigate ENIGMAs genomic data. Initially started as a web page to plot ENIGMA summary statistics data for a specic
genomic region, ENIGMA-Vis grew over the years into a portal with tools to query, visualize, and navigate the effects, and relate them to other GWAS.
cIn complementary work on rare variants by the ENIGMA-CNV Working Group, Sønderby and colleagues (2018) examined effects of the 16p11.2
distal CNV that predisposes to psychiatric conditions including autism spectrum disorder and schizophrenia. ENIGMA (including the 16p11.2
European Consortium) and deCODE datasets were combined to discover negative dose-response associations with copy number on intracranial
volume and regional caudate, pallidum and putamen volumessuggesting a neuropathological pattern that may underlie the neurodevelopmental
syndromes. The agreement across datasets is apparent in the Forest plots for each brain region. [Data adapted, with permission from the authors and
publishers].
Thompson et al. Translational Psychiatry (2020) 10:100 Page 9 of 28
growth or atrophy, and performs GWAS to nd genetic
markers that may inuence these rates of change. The
ENIGMA-Plasticity WG has established the heritability of
brain changes over time and has shown that distinct
genetic factors inuence regional brain volumes and their
rate of change, implying the existence of genetic variants
specically associated with change
39
. The WG is further
investigating how closely developmental and aging-related
genes overlap, and how they overlap with genetic loci that
are associated with risk for development of psychiatric
and neurological disease throughout life. Overall, the high
rate of discovery driven by ENIGMA is offering initial
glimpses of the overlap among genetic drivers of brain
change throughout life with specic markers of brain
structure and function.
Uncovering the genetic basis of brain functional variation
The ENIGMA Consortium has also carried out genetic
association studies of EEG-derived phenotypes. The rst
study
40
of the EEG WG performed the largest GWAS to
date of oscillatory power across a range of frequencies
(delta 13.75 Hz, theta 47.75 Hz, alpha 812.75 Hz, and
beta 1330 Hz) in 8425 healthy subjects. They identied
several novel genetic variants associated with alpha
oscillatory brain activity that were previously linked to
psychiatric disorders.
Characterizing the association between brain morphology
and disease-risk genes
In an early ENIGMA study, minimal overlap was
detected between schizophrenia-related and brain-related
genetic loci
37
. These questions were revisited with Baye-
sian models
41
and LD-score regression methods
42
which
identied stronger overlap between genetic loci involved
in cortical structure and loci implicated in insomnia,
major depression, Parkinsons disease, and general cog-
nitive ability or IQ
13
. Despite initial negative results
37
,
ENIGMAs growing sample size led to more powerful
results, allowing for the recent successes in the discovery
of brain-related genetic variants that also affect risk for
schizophrenia
43,44
, OCD
45
, anxiety disorders
46
, PTSD
46
,
ADHD
47
, anorexia nervosa
48
, Tourette syndrome
49
, and
insomnia
13
.
As the sample size of brain scans in the ENIGMA
Consortium increased beyond 50,000 MRI scans, it
became possible to discover further genetic loci associated
with multiple brain traits implicated in brain disorders. A
recent example is an ENIGMA-CHARGE GWAS of white
matter (WM) hyperintensities, a sign of vascular brain
disease, by Mather et al. (in prep), which found hetero-
geneous effects for variants associated with lesions near
the ventricles versus lesions elsewhere in the brain. An
innovative feature of this analysis was the use of anato-
mical clustering of traits to yield more powerful brain
GWAS results. Anatomical or genetic clustering is yet
another methodological improvement implemented by
ENIGMA, that can be used widely to enhance detection of
genetic associations in multiple brain disorders (see Lor-
enzi, Couvy-Duchesne for other multivariate imaging
GWAS approaches
50,51
).
Uncovering the epigenetic basis of brain morphometric
variation
Inspired by these successes, ENIGMA widened the
scope of its WGs to embrace the study of epigenetic
variations. ENIGMAs Epigenetics group has already
identied two sites in the genome where methylation
relates to hippocampal volume (N=3337)
52
. Ongoing
studies focus on brain measures sensitive to epigenetic
age, an index of biological as opposed to chronological
aging, in both health and disease.
From common nucleotide variations to rare copy number
variants (CNV)
The ENIGMA-CNV WG was launched to study the
effects of CNVs, relatively rare genetic variants predis-
posing individuals to various neuropsychiatric disorders.
The ENIGMA collaborative approach is ideal for studying
low-frequency variants, as such efforts require large
samples that are usually beyond the scope of a single
study. Their rst reports were on the 16p11.2 distal
53
and
15q11.295 CNVs (Fig. 3) and additional studies on other
CNVs are underway.
ENIGMA disorder-based neuroimaging studies
ENIGMA-schizophrenia
The Schizophrenia WG was formed in 2012, and has
since analyzed data from 39 cohorts worldwide and has
identied casecontrol differences in brain morpho-
metry
1,54,55
and WM microstructure
56,57
, on an unpre-
cedented scale. ENIGMA-Schizophrenia was the rst
working group to publish large-scale analyses of disease,
in two seminal papers on casecontrol differences in
brain morphometry based on the largest samples to date.
Van Erp and ENIGMA colleagues
54
rst reported that
patients with SCZ (N=2028 patients) had smaller hip-
pocampus (Cohensd=0.46), amygdala (d=0.31),
thalamus (d=0.31), nucleus accumbens (d=0.25),
total intracranial volumes (d=0.12), and larger palli-
dum (d=0.21) and lateral ventricle volumes (d=0.37)
compared to healthy controls (N=2540). In a subsequent
study, the team expanded their sample to include 4474
individuals with SCZ and 5098 controls to study cortical
structures
1
. Compared to healthy controls, patients with
SCZ had globally thinner cortices (left/right hemisphere:
d=0.53/0.52) and smaller overall cortical surface area
(left/right hemisphere: d=0.25/0.25), with greatest
effect sizes in frontal and temporal regions.
Thompson et al. Translational Psychiatry (2020) 10:100 Page 10 of 28
Figures 4and 5present these cortical and subcortical
ndings alongside data from several other disorders. It is
notable that these ndings from ENIGMA
13,54
were
replicated in a large independent study by the Japanese
COCORO Consortium
58
, and a recent Norwegian study
of 16 cohorts by Alnæs et al.
59
. The convergence of all
three studies, reviewed in Kochunov et al.
60
, represents a
new level of rigor and reproducibility in a eld where the
existence of morphometric correlates of schizophrenia
was once hotly debated
61
.
Brain alterations were also discovered in relation to
clinical features of the disease. In follow-up analyses,
Walton et al. found that positive symptom severity was
negatively related to the thickness of the superior tem-
poral gyrus bilaterally
62
, while the severity of negative
symptoms was negatively related to the cortical thickness
of several prefrontal regions and particularly the left
medial orbitofrontal cortex (MOFC)
63
.
At this point it is worth considering the added value of
other data modalities, such as diffusion MRI, which offers
complementary information on microstructural abnorm-
alities, especially in the WM, that are not detectable on
standard anatomical MRI. ENIGMAs Diffusion MRI
working group, launched in 2012 with protocols for dif-
fusion tensor imaging (DTI), published a series of papers
on the heritability and reproducibility of DTI measures
derived with a protocol based on tract-based spatial sta-
tistics
6466
. Over ten of ENIGMAs working groups have
since used this protocol to rank effect sizes for DTI
metrics across key WM tracts.
Kelly et al. reported on widespread WM abnormalities
in schizophrenia, pooling data from 2359 healthy controls
and 1963 patients with SCZ from 29 independent inter-
national studies
56
. Signicant reductions in fractional
anisotropy (FA) in patients with SCZ were widespread
across major WM fasciculi. While effect sizes varied by
tract and included signicant reductions in the anterior
corona radiata (d=0.40) and corpus callosum (d=0.39,
specically its body (d=0.39) and genu (d=0.37)),
effects were observed throughout the brain, with peak
reductions observed for the entire WM skeleton (d=
0.42). Figure 6shows these ndings alongside data from
two other disorders for which ENIGMA published large-
scale DTI analyses, MDD
67
, and 22q11DS
17
.
Fig. 4 ENIGMAs large-scale studies of nine brain disorders. Cortical gray matter thickness abnormalities as Cohensd, are mapped for nine
different disorders, for which worldwide data were analyzed with the same harmonized methods. Although the cohorts included in the studies
differed, as did the scanning sites and age ranges studied, some common and distinct patterns are apparent. Cortical maps for major depressive
disorder (MDD), bipolar disorder (BD) and schizophrenia show gradually more extensive proles of decits. Across all disorders, the less prevalent
disorders tend to show greater effects in the brain: the relatively subtle pattern of hippocampal-limbic decits in MDD broadens to include frontal
decits in bipolar disorder (consistent with frontal lobe dysfunction and impaired self-control). In schizophrenia, decits widen to include almost the
entire cortexonly the primary visual cortex (specically the calcarine cortex) failed to show thickness alterations in patients, after meta-analysis.
Autism spectrum disorder (ASD) and the 22q deletion syndrome (22q11DS)a risk condition for ASDare associated with hypertrophy in frontal
brain regions, while patients with obsessive-compulsive disorder (OCD) and alcohol use disorder tend to show decits in frontal brain regions
involved in self-control and inhibition. More rened analyses are now relating symptom domains to these and other brain metrics, within and across
these and other disorders.
Thompson et al. Translational Psychiatry (2020) 10:100 Page 11 of 28
ENIGMA-BD
Formed shortly after the Schizophrenia WG, and fol-
lowing similar protocols, the ENIGMAs BD WG reported
on cortical thickness and surface area measures using
anatomical MRI data from 1837 adults with BD and 2582
healthy controls, from 28 international groups
68
. BD was
associated with reduced cortical thickness in bilateral
frontal, temporal and parietal regions, and particularly in
the left pars opercularis (d=0.29), the left fusiform
gyrus (d=0.29), and left rostral middle frontal cortex
(d=0.28). Interestingly, lithium use was associated with
thicker cortex in several areas. The WG also examined
casecontrol differences in subcortical volumes in 1710
patients with BD and 2594 healthy controls; they found
that BD was associated with reductions in the volume of
the hippocampus (d=0.23) and the thalamus (d=
0.15), and with enlarged lateral ventricular volume (d=
0.26). A follow-up study, showed that when applied to
regional cortical thickness, surface area, and subcortical
volumes, machine learning methods (based on support
vector machines) differentiated BD participants from
controls with above chance accuracy even in a large and
heterogeneous sample of 3020 participants from 13
ENIGMA cohorts worldwide
23
. Aggregate analyses of
Fig. 5 Subcortical abnormalities in schizophrenia, bipolar
disorder, major depressive disorder, and ADHD. a ENIGMAs
publications of the three largest neuroimaging papers on
schizophrenia (SCZ), bipolar disorder (BD), and major depressive
disorder (MDD), suggested widespread cross-disorder differences in
effects (van Erp et al.
54
, Hibar et al.
68
). By processing 21,199 peoples
brain MRI scans consistently, we found greater brain structural
abnormalities in SCZ and BD versus MDD, and a very different pattern
in attention-decit/hyperactivity disorder (ADHD; Hoogman et al.
7
).
Subcortically, all three disorders involve hippocampal volume decits
greatest in SCZ, least in MDD, and intermediate in BD. As a slightly
simplied rule of thumb, the hippocampus, ventricles, thalamus,
amygdala and nucleus accumbens show volume reductions in MDD
that are around half the magnitude of those seen in BD, which in turn
are about half the magnitude of those seen in SCZ. The basal ganglia
are an exception to this ruleperhaps because some antipsychotic
treatments have hypertrophic effects on the basal ganglia, leading to
volume excesses in medicated patients. In ADHD, however, the
amygdala, caudate and putamen, and nucleus accumbens all show
decits, as does ICV (ventricular data is not included here for ADHD, as
it was not measured in the ADHD study). A web portal, the ENIGMA
Viewer, provides access to these summary statistics from ENIGMAs
published studies of psychiatric and neurological disorders (http://
enigma-viewer.org/About_the_projects.html). bIndependent work by
the Japanese Consortium, COCORO, found a very similar set of effect
sizes for group differences in subcortical volumes between
schizophrenia patients and matched controls.
Fig. 6 White matter microstructure in schizophrenia, major
depressive disorder, and 22q11.2 deletion syndrome. a White
matter microstructural abnormalities are shown, by tract, based on the
largest-ever diffusion MRI studies of these three disorders. In
schizophrenia (SCZ), fractional anisotropy, a measure of white matter
microstructure, is lower in almost all individual regions, and in the full
skeleton. In major depressive disorder (MDD), a weak pattern of effects
is observed, again with MDD patients showing on average lower FA
across the full white matter skeleton, when compared to controls. In
comparisons between 22q11.2 deletion syndrome (22q11DS) and
matched controls, by contrast, the average FA along the full white
matter skeleton does not show systematic differences; instead, while
some regions do show on average lower FA in affected individuals
compared with controls, several white matter regions show higher FA.
bRelative to appropriately matched groups of healthy controls (HC),
group differences in fractional anisotropy are shown for ENIGMAs
studies of SCZ, MDD (both in adults), and 22q11.2 deletion syndrome.
[Data adapted, with permission of the authors and publishers, from
Kelly et al.
56
, van Velzen et al.
67
, and Villalón-Reina et al.
17
; a key to the
tract names appears in the original papers; some tracts (i.e. the
hippocampal portion of the cingulum) were omitted from the
22q11DS analysis as they were not consistently in the eld of view for
some cohorts of the working group].
Thompson et al. Translational Psychiatry (2020) 10:100 Page 12 of 28
individual subject data yielded better performance than
meta-analysis of site-level results. Age and exposure to
anticonvulsants were associated with greater odds of
correct classication. Although short of the 80% clinically
relevant threshold, the 65.2% accuracy (0.71 ROC-AUC)
is promising, as the study focused on a difcult to diag-
nose, highly heterogeneous condition and used only
engineered features, not raw brain imaging data. ENIG-
MAs multi-site design may also offer a more realistic
assessment of real-worldaccuracy, by repeatedly leaving
out different sitesdata for cross-validation. Future mul-
tisite brain-imaging machine learning studies will begin to
move towards sharing of more detailed individual subject
data, not only a selection of discrete features or site-level
results derived from a single modality; unsupervised
machine learning techniques may offer potential to better
understand the heterogeneity in the disorder. The
ENIGMA-BD DTI WG conducted both a mega- and
meta-analysis of 3033 subjects (1482 BD and 1551 con-
trols)
69
. Both analyses found lower FA in patients with BD
compared with healthy controls in most brain regions,
with the highest effect sizes in the corpus callosum and
cingulum.
ENIGMA-MDD
Brain morphometric analyses conducted by the
ENIGMA-MDD WG were based on MRI data from 1728
patients with MDD and 7199 controls for subcortical
volumes
70
and from 2148 patients with MDD and 7957
controls for cortical measures
3
. These studies found that
patients with MDD had lower hippocampal volumes (d=
0.14), an effect driven by patients with recurrent illness
(d=0.17) and by patients with an adolescent (21
years) age of onset (d=0.20). First-episode patients
showed no subcortical volume differences compared to
controls. Adult patients (>21 years) had reduced cortical
thickness in bilateral orbitofrontal cortex (OFC), anterior
and posterior cingulate cortex, insula, and temporal lobe
regions (ds: 0.10 to 0.14). In contrast, adolescent
patients showed no differences in cortical thickness but
showed lower total surface area, which seemed to be
especially driven by lower surface area in frontal (medial
OFC and superior frontal gyrus), visual, somatosensory,
and motor areas (d=0.26 to 0.57). Moreover, these
differences in gray matter morphometry observed in
MDD do not involve abnormal asymmetry, as shown in a
joint study by the Laterality and the MDD WGs involving
2540 MDD individuals and 4230 controls, from 32
datasets
71
.
A follow-up analysis on a subset of these aforemen-
tioned data found that the brain MRIs of adult patients
with MDD (1875 years old) appeared, on average, 1.08
years older than those of controls (d=0.14)
72
. This brain
ageestimate was based on a machine learning algorithm
trained to predict chronological age from morphometric
data from 2188 controls across 19 cohorts and subse-
quently applied to hold-out data from 2126 healthy con-
trols and 2675 people with MDD. The largest brain aging
effects were observed in antidepressant users (+1.4 years;
d=0.15), currently depressed (+1.5 years; d=0.18), and
remitted patients (+2.2 years; d=0.18), compared to
controls. Within ENIGMA-MDD, Opel et al. also studied
the effects of obesity on structural brain metrics of
patients and controls (N=6420)
73
. Obesity effects were
not different between patients and controls, but there was
a signicant obesity by age interaction in relation to
cortical thickness, with thinner cortices in older obese
individuals. Cortical thickness decits related to obesity
were strongest in the temporal and frontal cortical
regions, and overlapped with patterns observed in several
neuropsychiatric disorders, but exceeded those found in
MDD without regard for BMIin terms of the effect sizes
and range of structures affected. The magnitude of these
effects suggests a need to better understand the connec-
tions between BMI, brain aging and mental health.
Capitalizing on the statistical power of ENIGMA to
examine the role of risk factors, Frodl
74
and Tozzi
75
examined the association between retrospectively assessed
childhood maltreatment (including emotional, physical and
sexual abuse, or emotional and physical neglect), and brain
morphometry in 3036 and 3872 individuals (aged 1389)
with and without MDD, respectively. Greater exposure to
childhood maltreatment was associated with lower cortical
thicknessofthebanksofthesuperior temporal sulcus and
supramarginal gyrus, and with lower surface area across the
whole brain and in the middle temporal gyrus. Sex differ-
ences were also observed: in females, greater maltreatment
severity was associated with overall lower gray matter
thickness and smaller caudate volumes, whereas in males,
greater maltreatment severity was associated with lower
thickness of the rostral anterior cingulate cortex.
In addition to these investigations of gray matter in
MDD, a large-scale analysis of WM microstructure with
DTI has also been completed, comparing 1305 adults and
adolescents with MDD to 1602 healthy controls from
20 samples worldwide
67
. In adults with MDD, widespread
lower FA values were found in 16 out of 25 WM tracts of
interest (ds=0.120.26), with the largest differences in
the corpus callosum and corona radiata. Widespread
increased radial diffusivity (RD) was also observed (ds=
0.120.18) and was driven by patients with recurrent
MDD and an adult-onset of depression.
ENIGMA-PGC Post-Traumatic Stress Disorder
In partnership with the PGC, ENIGMA launched a WG
on PTSD that has analyzed neuroimaging and clinical
data from 1868 individuals (including 794 patients with
PTSD) from 16 cohorts. In this rst ENIGMA-PTSD
Thompson et al. Translational Psychiatry (2020) 10:100 Page 13 of 28
study, Logue and colleagues found that patients with
current PTSD had smaller hippocampal volumes (d=
0.17) compared to trauma-exposed controls
4
. Child-
hood trauma predicted smaller hippocampal volume (d=
0.17) independent of diagnosis. In a subsequent study,
the WG found that cortical thickness in 3378 individuals
(including 1309 patients with PTSD) was lower in PTSD
in the orbitofrontal cortex, cingulate cortex, precuneus,
insula, and lateral parietal cortices. In addition, a DTI
meta-analysis of 3057 individuals (including 1405 patients
with PTSD) from 25 cohorts found alterations in WM
organization in the tapetum, a structure that connects the
left and right hippocampus
76
. Structural covariance net-
work analysis applied to data from 3505 individuals
(including 1344 patients with PTSD), which examined
correlated patterns of cortical thickness and surface area,
found that PTSD is associated with network centrality
features of the insula and visual association areas
77
.To
extend these ndings, ongoing studies are assessing cor-
tical structure
78,79
and hippocampal subelds in PTSD
and MDD
8083
, to better understand the pattern and
regional specicity of hippocampal decits in the two
disorders, and whether these patterns coincide.
ENIGMA-Addictions/SUD
The ENIGMA-Addictions/SUDs WG has 33 partici-
pating sites, contributing MRI data from 12,347 indivi-
duals of whom 2277 are adult patients with SUD relating
to one of ve substances (alcohol, nicotine, cocaine,
methamphetamine, or cannabis)
5,84,85
. In these data,
Mackey
5
observed lower cortical thickness/subcortical
volume in cases relative to controls in regions that play
key roles in evaluating reward (MOFC, amygdala), task
monitoring (superior frontal cortex), attention (superior
parietal cortex, posterior cingulate) and perception/reg-
ulation of internal body states (insula). While the most
pervasive casecontrol differences appeared to be related
to alcohol dependence, some effects were observed for
substance dependence generally (e.g., the insula and
MOFC). A support vector machine trained on cortical
thickness and subcortical volume successfully classied
set-aside test sets for both alcohol (ROC-AUC: 0.740.78;
p< 0.0001) and nicotine dependence (ROC-AUC:
0.600.64; p< 0.0001), relative to non-dependent con-
trols
5
. A separate meta-analysis also compared the effect
size of addiction-related brain impairment to that of other
psychiatric disorders: effect sizes of alcohol-related brain
differences in subcortical brain regions were equivalent to
those reported for schizophrenia
86
.
ENIGMA-Obsessive-Compulsive Disorder
The ENIGMAs OCD WG grew out of a previously
established consortium (the OCD Brain Imaging Con-
sortium, or OBIC)
87
, and has published the largest studies
to date of brain structure in adult and pediatric OCD,
using both meta- and mega-analytic approaches
6,88
. The
rst study analyzed MRI scans from 1830 patients diag-
nosed with OCD and 1759 controls across 35 cohorts
from 26 sites worldwide
88
. Unmedicated pediatric OCD
patients demonstrated larger thalamic volumes, while the
pallidum was enlarged in adult OCD patients with disease
onset at childhood. Adult OCD patients also had sig-
nicantly smaller hippocampal volumes (d=0.13), with
stronger effects in medicated patients with adult-onset
OCD compared to healthy controls (d=0.29). A cor-
tical study included data from 1905 patients diagnosed
with OCD and 1760 healthy controls across 38 cohorts
from 27 sites worldwide. In adult patients diagnosed with
OCD versus controls, signicantly smaller surface area of
the transverse temporal cortex (d=0.16) and a thinner
inferior parietal cortex (d=0.14) were found. Medi-
cated adult patients with OCD also showed thinner cor-
tices throughout the brain (Cohensdeffect sizes varied
between 0.10 and 0.26). Pediatric patients with OCD
showed signicantly thinner inferior and superior parietal
cortices (ds=0.24 to 0.31), but none of the regions
analyzed showed signicant differences in cortical surface
area. However, medicated pediatric patients with OCD
had smaller surface area in frontal regions (ds=0.27 to
0.33), that may indicate a delayed cortical maturation.
The absence of cortical surface area abnormalities in adult
patients with a childhood onset of OCD could indicate a
normalization of these abnormalitiesa hypothesis that is
now being explored with longitudinal data collection.
To assess whether the anatomical differences could be
used to create a neuroimaging biomarker for OCD, a
machine learning analysis of the cortical and subcortical
data was performed with 2304 OCD patients and 2068
controls. Classication performance across ten different
machine and deep learning approaches was poor. With
site-stratied cross-validation, the ROC-AUC ranged
between 0.57 and 0.62. The performance dropped to
chance level when leave-one-site-out cross-validation was
used, with classication performance between 0.51 and
0.54. This indicates that these anatomical brain features
do not provide a biomarker for OCD. But when patients
were stratied according to whether they had used med-
ication, classication performance improved remarkably.
Medicated OCD patients and controls could then be
distinguished with 0.73, unmedicated OCD and controls
with 0.61, and medicated and unmedicated OCD patients
with 0.86 ROC-AUC. These multivariate results therefore
mirror the univariate results, and highlight that medica-
tion use is associated with large differences in brain
anatomy
89
.
The OCD WG, in conjunction with the Laterality WG,
studied brain asymmetry in OCD using 16 pediatric
datasets (501 patients with OCD and 439 healthy
Thompson et al. Translational Psychiatry (2020) 10:100 Page 14 of 28
controls), and 30 adult datasets (1777 patients and 1654
controls)
90
. In the pediatric datasets, the largest
casecontrol differences were observed for volume
asymmetry of the thalamus (more leftward in patients
compared to controls; d=0.19) and the pallidum (less
leftward in patients compared to controls; d=0.21). No
asymmetry differences were found in the adult datasets.
These ndings may reect altered neurodevelopmental
processes in OCD, affecting cortico-striato-thalamo-
cortical circuitry, which is involved in a wide range of
cognitive, motivational and emotional processes.
ENIGMA-Attention-Decit/Hyperactivity Disorder
ENIGMAs ADHD WG has analyzed data from up to
2264 participants with ADHD and 1934 controls from up
to 36 sites (age range: 463 years; 66% males)
91
. Volumes
of the nucleus accumbens (d=0.15), amygdala (d=
0.19), caudate (d=0.11), hippocampus (d=0.11),
putamen (d=0.14), and ICV (d=0.10) were smaller
in cases relative to controls. Effect sizes were highest in
children. No statistically signicant univariate case/con-
trol differences were detected in adults. Volume differ-
ences were found to have similar effect sizes in those
treated with psychostimulant medication and those naïve
to psychostimulants. Bioinformatics analyses suggested
that the selective subcortical brain region vulnerability
was associated with differential expression of oxidative
stress, neurodevelopment and autophagy pathways
92
.
The ENIGMA-ADHD WG was the rst WG in
ENIGMA to perform a detailed investigation of the case-
control effects on the cerebellum. Differential age trajec-
tories were identied for children with ADHD when
compared with typically developing children for the cor-
pus medullare
93
.
In an analysis of the cerebral cortex, lower surface area
values were found, on average, in children with ADHD,
mainly in frontal, cingulate, and temporal regions; the
largest effect was for total surface area (d=0.21).
Fusiform gyrus and temporal pole cortical thickness were
also lower in children with ADHD. All effects were most
pronounced in early childhood. Neither surface area nor
thickness differences were found in the adolescent or
adult groups
7
, but machine learning analyses supported
the hypothesis that the casecontrol differences observed
in childhood could be detected in adulthood
94
. Impor-
tantly, many of the same surface area features were
associated with subclinical ADHD symptoms in children
from the general population that do not have a clinical
psychiatric diagnosis. Several of the observed brain
alterations fullled many of the criteria of endopheno-
types(An endophenotype is a trait, such as brain struc-
ture or function, related to the biological process of a
disorder; to qualify as an endophenotype, the trait, should
be heritable, co-segregate with an illness, yet be present
even when the disease is not, and be found in non-affected
family members at a higher rate than in the general
population
95,96
), as they were also seen in unaffected
siblings of people with ADHD in a subsample analysis of
the cortical features. The stronger effects in children may
reect a developmental delay, perhaps due in part to
genetic risk factors, given recent ndings of overlap
between the genetic contributions to ADHD and to sub-
cortical volumes
13,47
.
ENIGMA-Autism Spectrum Disorders
The ENIGMA-ASD WG published the largest neuroi-
maging study of autism analyzing data from 1571 partici-
pants with ASD and 1651 controls, from 49 sites worldwide
(ages 264 years)
8
. Unlike most of the disorders discussed
so far, the direction of effects seen in ASD varied by brain
region, and did so across the age span analyzed. ASD was
associated with larger lateral ventricle and intracranial
volumes, greater frontal cortical thickness and lower tem-
poral cortical thickness (d=0.21 to 0.20). Participants
with ASD also had, on average, lower subcortical volumes
for the pallidum, putamen, amygdala, and nucleus accum-
bens. Post hoc fractional polynomial analyses showed a
sharp increase in volumes in the same regions in childhood,
peaking in adolescence and decreasing again in adulthood.
Overall, patients with ASD showed altered morphometry in
the cognitive and affective associated-regions of the stria-
tum, frontal cortex, and temporal cortex.
The ASD group worked together with the Laterality
group to produce the largest ever study of brain asym-
metry in ASD, involving 1774 patients and 1809 controls,
from 54 datasets
97
. Generally, subtle but widespread
reductions of cortical thickness asymmetries were present
in patients with ASD compared to controls, as well as
volume asymmetry of the putamen, and surface area
asymmetry of the MOFC (the strongest effect had
Cohensd=0.16). Altered lateralized neurodevelop-
ment may, therefore, be a feature of ASD, affecting
widespread cortical regions with diverse functions.
Neurogenetic disorders, CNV, and rare
neurodevelopmental conditions
Several neurodevelopmental disorders arise due to the
abnormal duplication or deletion of segments of the gen-
ome. ENIGMA has dedicated WGs studying 22q11DS,
Gauchers disease, and Hepatic Glycogen storage dis-
ease
98,99
, along with a CNV WG meta-analyzing imaging
data from carriers of several other CNVs
53,100
. Here, we
focus on the work of the two most established groups, that
examine carriers of 22q11.2 deletions and other CNVs.
ENIGMA-22q11.2 Deletion Syndrome
22q11DS is associated with a 20-fold increased risk for
psychosis, and an elevated risk for developmental
Thompson et al. Translational Psychiatry (2020) 10:100 Page 15 of 28
neuropsychiatric disorders such as ASD. 22q11DS provides
agenetics-rstframework to study the brain markers
underlying complex psychiatric phenotypes. The ENIGMA-
22q11DS working group analyzed the largest dataset to date
of brain images from patients with 22q11DS from 10
cohorts including 466 individuals with 22q11DS and 374
matched controls. Compared to controls, 22q11DS indivi-
duals showed overall thicker cortical gray matter (left/right
hemispheres: Cohensd=0.61/0.65), but pervasive reduc-
tions in cortical area (left/right hemispheres: d=1.01/
1.02), with specic anatomic patterns. Machine learning
methods were applied to the cortical thickness and area
measures to achieve a high accuracy (sensitivity 94.2%;
specicity 93.3%) in classifying 22q11DS cases and con-
trols
10
. ENIGMA subcortical shape analysis pipelines also
identied complex structural differences across many sub-
cortical structures between individuals with 22q11DS and
controls
101
. Analysis of diffusion MRI from the same sub-
jects (N=594) revealed abnormalities in the corpus callo-
sum, superior longitudinal fasciculus, and corona radiata
17
.
Ongoing work uses more advanced imaging protocols
17
including multishelldiffusion protocols that allow for the
estimation of biophysical compartments in the tissueto
test hypotheses about specic cellular processes and specic
ber tracts that may be especially vulnerable in 22q11DS
(e.g., the corpus callosum), as well as ber tracts that appear
to be relatively spared (e.g., the cortico-fugal tracts
17
).
ENIGMA-Copy Number Variations
This WG was set up to examine the effect of rare CNVs,
risk factors for a variety of neuropsychiatric disorders, on
brain structure. Due to their low prevalence
102,103
, their
effects on the brain have been hard to establish. Sønderby
and colleagues focused on the 16p11.2 distal CNV that
predisposes to psychiatric conditions including ASD and
schizophrenia. ENIGMA (including the 16p11.2 European
Consortium) and deCODE datasets were combined to
compare subcortical brain volumes of carriers of 15
16p11.2 distal deletion and 18 duplication to 7714 non-
carriers which led to the discovery of negative dose-
response associations with copy number on intracranial
volume and regional accumbens, caudate, pallidum and
putamen volumessuggesting a neuropathological pat-
tern that may underlie the neurodevelopmental syn-
dromes
53
. A further study
100
including the UK Biobank
assessed the association of the 15q11.2 CNV with cogni-
tion and cortical and subcortical morphology in more
than 45,000 individuals from 38 datasets (203 individuals
with a 15q11.2 deletion, 45,247 non-carriers, and 306
duplication carriers). The authors found a clear pattern of
widespread poorer cognitive performance, smaller surface
area and thicker cortices for deletion carriers compared to
non-carriers and duplication carriers, particularly across
the frontal lobe, anterior cingulate and pre/postcentral
gyri. The pattern of results ts well with known molecular
functions of the genes in the 15q11 region and suggests
involvement of these genes in neuronal plasticity and
cortical development. Thus, the results from ENIGMA-
CNV have shown that several CNVs cause abnormal brain
patterns and inform on genetically determined variation
in brain development and their relation to neurodeve-
lopmental disorders. Additional studies on other CNVs
are in progress.
Newly established working groups
In the last two years, seven additional ENIGMA WGs
have formed to study specic disorders and important
transdiagnostic conditions: anxiety disorders, suicidal
thoughts and behavior, sleep and insomnia, eating dis-
orders (including bulimia and anorexia nervosa sub-
groups
104
), irritability, antisocial behavior, and
dissociative identity disorder. The starting point of the
anxiety group was an international voxel-based morpho-
metry mega-analysis on social anxiety disorder
105
, sup-
ported by ndings demonstrating that structural brain
alterations related to social anxiety run in families
106
.At
present, the anxiety WG has four subgroups including
over 5000 patients: besides social anxiety disorder (1250
patients)
107
, there are groups devoted to generalized
anxiety disorder (1329 patients), panic disorder (1300
patients), and specic phobia (1224 patients), allowing for
disorder-specic and cross-disorder comparisons. The
antisocial behavior WG aims to clarify how conduct dis-
order, psychopathy, and antisocial personality disorder
relate to differences in brain structure, function, and
connectivity. Its goals include examination of different
phenotypes (e.g., reactive vs proactive aggression),
population-based samples with dimensional measures of
antisocial behavior, and genetic data from casecontrol
and population-based studies.
Building on the promising ndings from the psychiatric
WGs, ENIGMA established seven WGs studying specic
conditions in neurology and cancer-related cognitive
impairment: epilepsy, traumatic brain injury, Parkinsons
disease, neuro-HIV, ataxia, stroke recovery, and cancer/
chemotherapy effects on the brain
108,109
.
ENIGMA-Epilepsy
The ENIGMA-Epilepsy WG combined data from 24
centers across 14 countries to create the largest neuroi-
maging study to date of epilepsy
9
. Data from 2149 indi-
viduals with epilepsy were divided into four common
epilepsy syndromes: idiopathic generalized epilepsies (N
=367), mesial temporal lobe epilepsies with hippocampal
sclerosis (MTLE; left, N=415; right, N=339), and all
other epilepsies in aggregate (N=1026), compared to
1727 matched healthy controls. Compared to controls, all
epilepsy groups showed lower volume in the right
Thompson et al. Translational Psychiatry (2020) 10:100 Page 16 of 28
thalamus (d=0.24 to 0.73), and lower thickness in the
precentral gyri bilaterally (d=0.34 to 0.52). Both
MTLE subgroups also showed profound volume reduc-
tion in the ipsilateral hippocampus (d=1.73 to 1.91),
and lower thickness in cortical regions, including the
precentral and paracentral gyri (d=0.36 to 0.52)
compared to controls. Notably, the effect sizes for cortical
differences in this neurological disorder were much
greater than those seen in all complex psychiatric dis-
orders. In an approach known as virtual histology,a
follow-up study
110
overlaid the cortical decit maps on
gene-expression data from the Allen Brain Atlas, and
detected enrichment for microglial markers in regions
with greater decits. The WG is currently combining DTI
data and exploring putative neuroanatomical biomarkers
of medication treatment resistance and post-operative
outcomes.
ENIGMA-Brain Injury
ENIGMAs Brain Injury WG
111
combines data from 72
centers, and is organized into ten separate subgroups that
focus on (1) acute mild traumatic brain injury (TBI), (2)
adult moderate/severe TBI
112
, (3) pediatric moderate/
severe TBI
113,114
, (4) military-related brain injury
115118
,
(5) sports-related concussion
119
, (6) intimate partner
violence
120
, (7) MR spectroscopy
121
, (8) arterial spin
labeling, (9) resting state fMRI, and (10) cognitive end-
points. These groups have recently started-up compared
to other ENIGMA WGs, but are rapidly expanding in
membership and focus. In addition to meta- and mega-
analyses of relevant existing datasets, the Brain Injury
WGs endeavor to further extend efforts to promote
increased consistency in prospective data collection, both
in terms of imaging data and associated cognitive out-
come data. Additionally, the WGs are engaged in the
development of novel pipelines and analytic tools that
address brain-injury specic issues or incorporate
sequences or techniques that are potentially useful in
addressing injury associated pathology. For example,
future planned studies will compute structural pathology
proles for individual TBI patients, including (i) mapping
of the heterogeneous lesions using advanced lesion
mapping methods (such as disconnectome symptom
mapping), (ii) accurate quantication of brain atrophy (of
the different brain regions) using tensor based morpho-
metry, and (iii) identication of subject-specic epicenters
best predictive of neurodegeneration using network
spread models. Finally, the Brain Injury WGs will inter-
face with other disease-specic WGs where comorbidity
with brain injury is high (e.g., substance use, PTSD, MDD,
ADHD), as well as with methods-focused WGs (e.g., dif-
fusion imaging, etc.). A preliminary report on 117 parti-
cipants with military-relevant blast-related versus 227
participants with non-blast related injury revealed higher
FA in veterans and service members with blast-related
injuries, and altered subcortical volumes in the group with
military TBI overall
117
. Work is ongoing to study the
effects of injuries sustained during and outside deploy-
ment, and severity and mechanisms of injury.
ENIGMA-Parkinsons Disease
ENIGMAs Parkinsons disease WG has analyzed scans
from 11 cohorts spanning 10 countries including 1288
patients with PD and 679 controls (age: 2089
years)
122,123
. A PD diagnosis was associated with moder-
ately larger thalamic volumes (left: d=0.29; right: d=
0.17) and smaller pallidal volumes (left: d=0.25; right:
d=0.21). There was also widespread and lower cortical
thickness in PD patients, while sparing the limbic and
insular cortices. Ongoing work on a larger sample is
relating brain structure and WM microstructure to dis-
ease severity, medication status and history and duration
of the illness as modiers of these robust differences
between patients and controls.
ENIGMA-Human Immunodeciency Virus
The availability of combination antiretroviral therapy
(cART) has now transformed HIV-infection from a pos-
sibly fatal diagnosis to a chronic condition, allowing for
viral suppression and stable immune function; however,
despite inconsistencies in neuroimaging studies, neuro-
logical symptoms and consequences persist. This WG has
pooled data from 12 independent neuro-HIV studies from
Africa, Asia, Australia, Europe, and North America;
volume estimates for eight subcortical brain regions were
extracted from anatomical MRI from 1044 HIV +adults
(age: 2281 years) to identify associations with plasma
markers reecting immunosuppression (CD4+T-cell
count) or viral load
124
. Across participants, lower cur-
rent CD4+count was associated with smaller hippo-
campal and thalamic volumes. A detectable viral load was
also associated with smaller hippocampal (d=0.24) and
amygdalar volumes (d=0.18), supporting the importance
of achieving viral suppression and immune restoration.
These limbic effects are in contrast to many of the early
neuro-HIV ndings that focused on basal ganglia struc-
tures, yet we found the limbic associations were largely
driven by participants on cART, while basal ganglia effects
(putamen) were detected in the subset of participants not
on cART. These ndings demonstrate the continuing
effects of HIV on the brain in the current cART era.
Alterations in brain structures that are essential for
learning and memory has clinical signicance given
mounting evidence of HIV-associated decits in these
cognitive domains among older HIV+adults, and the
possibility that HIV may contribute to abnormal brain
aging
125
.
Thompson et al. Translational Psychiatry (2020) 10:100 Page 17 of 28
ENIGMA-Ataxia
This WG includes 21 sites pooling data from more than
750 individuals with inherited ataxias, including Frie-
dreich Ataxia and Spinocerebellar Ataxia (SCA) 1, 2, 3, 6,
and 7 (the poly-glutamine SCAs), alongside over 800
controls. This group is undertaking optimization and
standardization of protocols for cerebellar voxel-based
morphometry and parcellation, upper spinal cord cross-
sectional area, and brainstem volume, in line with the key
regions of pathology in these diseases. Preliminary work
indicates that gray matter degeneration principally
impacts the cerebellar anterior lobe in Friedreich ataxia,
while all areas of the cerebellum are affected in the poly-
glutamine SCAs. However, both the magnitude and pat-
tern of cerebellar gray matter degeneration are distinct
across these diseases and evolve with disease progression
and severity.
ENIGMA-Stroke Recovery
The ENIGMA-Stroke recovery WG has addressed a
major gap in stroke research relating to the large-scale
denition of lesion masks. Researchers in this WG have
released a public archive of 304 T1-weighted MRIs with
manually segmented stroke lesion masks
126
(https://www.
icpsr.umich.edu/icpsrweb/ADDEP/studies/36684), and
developed open-source software
127
and analyses specic
for scalable
128
, reproducible lesion analyses (https://
github.com/npnl/PALS). In addition to this major meth-
odological contribution they have analyzed data from 629
participants from 22 sites worldwide to identify reliable
predictors of motor function after stroke
129,130
. They
found that motor-related subcortical volumes in the basal
ganglia and thalamus are positively associated with post-
stroke motor performance, and depend on impairment
severity, time since stroke, and lesion laterality. In con-
trast, enlarged lateral ventricles are associated with worse
post-stroke motor outcomes. The group now has data
from 1625 participants from 32 sites worldwide, and
ongoing work in the group focuses on quantifying lesion
overlap with major motor-related structures, such as the
corticospinal tracts and subcortical regions
131,132
, and
relating these measures with subcortical volumetric
measures to motor outcomes
133
.
ENIGMA-methods focused working groups
The ENIGMA Consortium functions as a driving force
for the development, validation and implementation of
novel methods to address the complexities of analyses of
large imaging datasets and to derive more mechanistic
insights into the processes that underpin variation in
brain organization in health and disease. To achieve this,
ENIGMA has dedicated WGs focused on the develop-
ment of more innovative pipelines for data analyses to be
applied for various dataset worldwide. The ENIGMA
Diffusion MRI WG on DTI is one of the most long-
standing. DTI offers information on microstructural
abnormalities that are not detectable on standard anato-
mical MRI. As mentioned earlier, this WG has published a
series of papers on the heritability and reproducibility of
DTI measures derived with a custom protocol based on
tract-based spatial statistics
64,134
. Diagnosis-based WGs
have used this protocol to rank effect sizes for DTI
metrics as previously described or are undertaking similar
studies including in 22q11DS
17
, epilepsy, PTSD
76
, military
TBI
113
, HIV
135
, and OCD
136
.
Other methodological WGs have focused on anatomical
shape analyses that enable a more precise characterization
of regional brain alterations thus resolving subregional
effects in the basal ganglia, amygdala, and hippo-
campus
55,85,137142
. Other approaches currently used in
ENIGMA include brain structural covariance analysis graph
theory approach for intra-individual brain structural cov-
ariance networks in OCD
77,143
, sulcal morphometry
144
,
hippocampal subeld analysis
8082,145
and disease effects on
lateralization (in OCD, MDD, and ASD)
71,90,97
.More
recently, ENIGMAs Brain Age WG was formed to apply
various algorithmic estimators of brain ageacross several
ENIGMA WGs
72
. From the ENIGMA-Brain Injury group,
the MR spectroscopy (MRS) WG has formed to focus on
the harmonization of MRS data which could reach across
other WGs in the future.
The impact of ENIGMA
The ENIGMA Consortium has been a driving force in
the eld of neuroscience by making substantial con-
tributions to the science of brain variation and shaping
the working practices of the eld at various levels. In
reecting on the key achievements, three areas stand out:
Promoting robustness and reproducibility
ENIGMAsbig dataapproach to neuroimaging
addresses directly the reproducibility challenges that pla-
gue many areas of biomedical scienceincluding neu-
roscience
146148
. Neuroimaging has received considerable
scrutiny regarding the reliability of published ndings,
given the literature replete with studies based on small
samples and seemingly unlimited methodological free-
dom
149,150
. Many other approaches also aim to tackle this
reproducibility crisis, by building data repositories that can
be accessed for replication
151153
; yet ENIGMA offers an
opportunity to collaborate with teams of diverse experts
irrespective of whether or not any data is shared. In one
recent study by ENIGMAs Laterality group, the authors
examined brain asymmetry in 99 MRI datasets worldwide
(from N=17,141 people) and found that, as expected, the
reproducibility of ndings increased with the effect size
and sample size, in a setting that was free from publication
bias (data available at: http://conxz.net/neurohemi/)
18,154
.
Thompson et al. Translational Psychiatry (2020) 10:100 Page 18 of 28
For example, for effect sizes of d0.6, the reproducibility
rate was higher than 90% even when including the datasets
with sample sizes as low as 15, while it was impossible to
obtain 70% reproducibility for small effects of d< 0.2, even
with a relatively large minimum sample size threshold of
500. The unprecedented size of the datasets analyzed
across ENIGMA boosts statistical power to detect the
effects of disease and their moderators
73,155
. Through data
sharing, investigators can now identify patterns of brain
abnormalities that consistently characterize disorders or
clinical syndromes, while assessing their reproducibility
across continents. This is exemplied by the close match
between the schizophrenia ndings by ENIGMA
54,60
and
independent work by the Japanese Consortium,
COCORO
58
and a recent Norwegian study of 16 cohorts
by Alnæs
59
. In all three studies, schizophrenia patients
showed enlargement of the lateral ventricles, pallidum,
putamen, and caudate, and volume reduction in the hip-
pocampus, amygdala, thalamus and accumbens, with a
strong agreement in the magnitude and rank order of
effects from highest to least group difference. Similarly, a
recent GWAS study of the UK Biobank dataset
156
was able
to replicate the majority of the genetic loci discovered by
ENIGMA in two separate GWAS of subcortical
volumes
24,25
. Thus, the international, multi-site nature of
ENIGMA studies likely promotes representative ndings
that are widely generalizable. Meanwhile, the larger and
more diverse samples are valuable resources for under-
standing the heterogeneity across different studies, and
may provide new insights into the reproducibility issue
faced by the neuroimaging community. Moreover,
ENIGMA offers a platform for investigators to converge
on methods for sharing and analyzing data acceptable to
the community.
ENIGMA also offers new opportunities to change the
landscape for how data can be used. In current research
practices, a great resource of data remains largely
untapped that is often known as long-taildata: data sets
collected in individual laboratories that accumulate over
many years and funding cycles
157
. Much valuable data
remains dormant (and unpublished) due to a lack of
personnel and time to analyze it, and this is going to
increase with studies including larger samples than before.
Efforts through ENIGMA to leverage dormantdata in
labs throughout the world have at least three important
advantages. First, data sharing increases the scope of the
science, enhancing opportunities for analyses not other-
wise possible with small sample sizes. Second, data shar-
ing naturally engages scientists from distinct disciplines
a crucial step for advancing the clinical neurosciences
158
.
Anal benet that is sometimes overlooked in global
scientic collaborations is their power to build and
enhance diplomatic relations and transcend political
conicts between nations
159
. With representation from 43
countriessome of which have minimal diplomatic ties
collaborations are not only constructive in terms of col-
lective problem solving, but they also build connections
between high income countries and the poorest nations
across the globe and to build capacity in the latter
159
.
Setting methodological standards
The ENIGMA Consortium has provided a blueprint for
multi-site standardization in terms of mining legacy
neuroimaging and genetic data. The success of this
approach is obvious when considering the volume of over
50 published works that has relied on the ENIGMA
pipelines. Furthermore, funding bodies, such as the
National Institutes of Health in the United States, have
gained interest in such approaches; program announce-
ments requesting applications on aggregating existing
biomedical data, or making use of existing resources, have
become increasingly common. Moving forward, ENIGMA
remains a test-bed of unprecedented scale and power for
developing and benchmarking novel analytic methods.
This contribution is of paramount importance as
advanced statistical modeling and bioinformatics become
essential for analytic pipelines. In efforts complementary
to the technical advances made in multisite data collec-
tion initiatives such as the Alzheimers Disease Neuroi-
maging Initiative, the Human Connectome Project, and
the UK Biobank, ENIGMAs studies have required us to
continually develop new scientic approaches to analyze
data from diverse and independent populations. ENIGMA
has made several technical advances that may be adapted
to other domains, including creating, adapting, and
extensively testing harmonized methods for distributed
analysis, meta-analysis, and cross-site data integration (see
Supplementary Appendix A: Technical Contributions of
ENIGMA).
Driving discovery
Neuroimaging and genetics are elds of both large and
small effects. For common, complex chronic diseases,
effects on brain metrics can be very subtle, but for rare
monogenic disorders and across the eld of neurology
including epilepsy, brain injury, stroke and neuro-oncol-
ogy, disease effects can be relatively large (although not
exclusively). In the 10 years since ENIGMA was founded,
the primary lesson has been on the power of worldwide
collaboration to discern subtle patterns in brain data, and
advance neuroscience beyond the capacity of any one
group of researchers collecting data on their own. New
discoveries regarding the factors that inuence brain
organization and its association with health and disease
are predicated on having adequate statistical power and
on developing new neuroimaging approaches aiming to
lead to more mechanistic explanations of the multi-scale
organization of the brain.
Thompson et al. Translational Psychiatry (2020) 10:100 Page 19 of 28
Challenges and future directions
Even given the advances made through ENIGMA dur-
ing its rst decade, as a growing consortium, ENIGMA
faces important challenges. Thus far, ENIGMA has largely
relied on existing data, which implies a degree of het-
erogeneity with respect to phenotypingincluding clin-
ical assessments, scanners and imaging protocols.
Another limitation of this type of data is that the depth of
phenotyping varies across centers, which can lead to a
limited set of clinical and other scales shared by all cen-
ters. As we discuss below, ENIGMA is now beginning to
address these limitations with a series of newly funded
and planned studies
111,112,114,118121
. The paucity of
longitudinal data in the literature is also reected within
ENIGMA, which includes a limited number of long-
itudinal studies. Consequently, the data-driven approach
used in ENIGMA is complementary, but not always
superior, to well-designed, hypothesis-driven, smaller-
scale prospective single-center or multi-center studies
with in-depth phenotyping.
Extending imaging modalities and computational
approaches
ENIGMAs future developments will include the coor-
dinated analyses of new data modalities (such as resting
state and task-related functional MRI
160163
, as well as
geostatistical and mobile sensor data), and deeper or more
rened analyses of current imaging modalities. Diffusion
MRI, in particular, is moving towards multi-shell proto-
cols that can better differentiate cellular and micro-
structural sources of variance that may explain patterns
observed with DTI
17
. Multimodal projects that pool data
across imaging modalities are likely to boost the accuracy
of machine learning methods for differential diagnosis,
outcome prediction, and subtyping. Unsupervised learn-
ingapplied to imaging and clinical datamay also help
to identify homogeneous subgroups within and across
disorders. Deep learning, for example, benets from very
large datasets, such as those analyzed in ENIGMA, and
these and other articial intelligence methods show pro-
mise in identifying unsuspected features and patterns in
images beyond those derived using traditional methods.
From its inception, ENIGMA has accommodated varying
data sharing practices across institutions and countries,
has used strategies (such as meta-analysis) to overcome
some of these, and is working with eld experts on novel
strategies (like COINSTAC or other distributed analysis
approaches)
164
to allow for more powerful analysis with-
out sending data around the globe. On the omicsside,
whole genome sequencing promises to rene our under-
standing of causal loci across all phenotypes, from plasma
markers and brain metrics to environmental exposure and
clinical measures of disease burden.
Cross-disorder analyses
ENIGMA has recently created cross-disorder groups to
answer transdiagnostic questions that draw on data from
multiple WGs
165
. An exemplar of this approach is the
newly formed ENIGMA-Relatives WG which examines
brain organization in the unaffected rst-degree relatives
of patients with psychiatric disorders. The rst study from
this group focused on identifying common and distinct
anatomical patterns in patients with SCZ (N=1016) or
BD (N=666) and their unaffected relatives (Nfor SCZ
relatives =1228 and for BD relatives =852)
11
.A
remarkable nding from this study is that the rst-degree
relatives of BD patients had larger ICV compared to
controls (d=0.16) while rst-degree relatives of SCZ
patients had smaller ICV and lower cortical thickness, and
when controlling for ICV, had regionally smaller thalamic
volumes. Other newly formed groups aim to aggregate
data across the spectrum of mental illness that may be
prone to similar symptoms and outcomes, such as suicidal
ideations and actions. Cross-disorder initiatives have
formed within ENIGMA as partnerships between existing
group members. The topology of collaboration (Fig. 7)
includes working partnerships between group members
working on similar problems, providing natural connec-
tions between topics of study of the different groups.
Sex differences
ENIGMAs sex differences Initiative is probing disease
WG datasets to better understand sex disparities in risk
factors, disease effects, or outcomes and their relationship
with brain organization. In a new initiative, the ENIGMA-
Transgender WG is contributing additional insights with
respect to the biological underpinnings of sex assigned at
birth versus gender identity
166
. The rst study from this
group was based on more than 800 scans and pooled
various MRI-based measures (cortical thickness, surface
area, and volume) across eight international sites. While
effects varied depending on the morphometric measure
applied and the brain regions considered, a general pat-
tern emerged: transgender men (assigned female at birth)
mostly resemble cis-gender women, whereas transgender
women (assigned male at birth) range between cis-gender
men and cis-gender women
167
. Ongoing initiatives
examining sex-differences focus on sex-specic GWAS
studies, and developmental and aging trajectories.
Global health disparities
Health disparities, including those that exist in low and
middle income countries, are also a topic of great interest
for ENIGMA, as prevalence, treatments, and access to
healthcare varies within and across countries. While the
analyses in ENIGMA so far tend to show cross-national
agreement in brain signatures and associated genetic loci
Thompson et al. Translational Psychiatry (2020) 10:100 Page 20 of 28
of various psychiatric diseases, more in-depth phenotyp-
ing may reveal circumstances where risk factors apply
more strongly to specic ethnic or sociodemographic
groups, and means to remediate them, consistent with the
concept of precision public health.
In closing, we reiterate ENIGMAs mission statement,
which reads: Individually, we contribute little to the quest
for truth, but working together, the whole vast world of
science is within our reach.(Aristotle, 350 BCE)
168
.
Acknowledgements
The work reported here was supported in part by many public and private
agencies across the world. Individual authorsfunding is listed in
Supplementary Appendix B. Core funding for ENIGMA was provided by the NIH
Big Data to Knowledge (BD2K) program under consortium grant U54
EB020403, by the ENIGMA World Aging Center (R56 AG058854), and by the
ENIGMA Sex Differences Initiative (R01 MH116147). Additional support was
provided by grants to the ENIGMA-PGC PTSD Working Group (R01 MH111671;
PI: RAM), the ENIGMA-Addiction Working Group (R01 DA047119; to H.P.G. and
P.J.C.), the ENIGMA Suicidal Thoughts and Behavior Working Group (R01
MH117601; to N.J. and L.S.), the ENIGMA Epilepsy Working Group (R01
NS107739; to C.R.M.), a genotyping grant from the Australian NHMRC
(APP1103623 and APP1158127; to SEM), a German federal grant to the ENIGMA
Task-Related fMRI Group (ER724/4-1 and WA1539/11-1; to H.W. and I.M.V.), a
Kavli Foundation Neuroscience without Borders seed grant (to N.J. and P.M.T.),
an NIH instrumentation grant (S10 OD023696 to P.K.), and K01 HD091283 (to S.
L.L.). We thank all scientists and participants in ENIGMA who made this work
possible. A full list of ENIGMA Consortium current and past members can be
found here http://enigma.ini.usc.edu/ongoing/members/.
Conict of interest
Individual authorsdisclosures and conicts of interest are listed in
Supplementary Appendix C.
Publishers note
Springer Nature remains neutral with regard to jurisdictional claims in
published maps and institutional afliations.
Supplementary Information accompanies this paper at (https://doi.org/
10.1038/s41398-020-0705-1).
Received: 3 July 2019 Revised: 11 December 2019 Accepted: 20 December
2019
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