pnas201910566 14384..14384


Correction

PROFILE
Correction for “Profile of Aravinda Chakravarti,” by Tinsley H.
Davis, which was first published May 6, 2019; 10.1073/
pnas.1906109116 (Proc. Natl. Acad. Sci. U.S.A. 116, 10608–10610).
The editors wish to note that on page 10609, Dr. C. C. Li was

described as a founder of the field of population genetics.
However, Dr. C. C. Li’s impact on the field was as an influential
figure rather than as a founder.

Published under the PNAS license.

Published online July 1, 2019.

www.pnas.org/cgi/doi/10.1073/pnas.1910566116

14384 | PNAS | July 9, 2019 | vol. 116 | no. 28 www.pnas.org

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PROFILE

Profile of Aravinda Chakravarti
Tinsley H. Davis, Science Writer

Many of the genetic variations uncovered by genome-
wide dragnets are bycatch, not primary disease
culprits. Separating causality from coincidence in this
sea of data is challenging, especially when many of the
candidates do not reside in the coding portion of the
genome. Aravinda Chakravarti, director of New York
University’s Center for Human Genetics and Geno-
mics, has made a career of not just cutting through
the noise but anticipating it, thanks to his training
in statistics and genetics. In his Inaugural Article,
Chakravarti, who was elected to the National Academy
of Sciences in 2015, outlines a systematic process for
determining causality in genome-wide association stud-
ies. He examines variants of regulatory elements that
control gene expression by focusing on variation in
cis-regulatory elements that target the SCN5A gene,
which is implicated in sudden cardiac death (1).

Finding Direction
Born in Calcutta, India in 1954, just seven years after the
country gained independence, Chakravarti remembers
a mood of optimism and a sense of possibility. “I grew
up in India at a very magical time.” Only in hindsight
would Chakravarti call his family’s financial circum-
stances poor. “I had every kind of material to read, from
national newspapers to glossy magazines to books,” he
says. “I grew up in a house where reading was very
valued, and curiosity was valued.”

Chakravarti attended a local high school run by
Methodist missionaries that offered advanced science
courses. After high school, Chakravarti applied to a
plethora of colleges. “I don’t know that I had a partic-
ular sense of direction,” he says. That changed as soon
as Chakravarti saw the first page of the Indian Statistical
Institute’s entrance examination, which contained two
10-digit numbers. The question asked which of five
possible answers resulted from multiplying the two
numbers. “It was obvious that the answer could not
be deduced by arithmetic—there was no time—but
logic,” says Chakravarti. “In India, the ability to advance
is the ability to take tests, but that’s not how science
advances.” The entrance examination hinted that his
soon-to-be alma mater “valued thinking and logic.”

During his time at the institute, Chakravarti re-
ceived a solid grounding in science and published his

first two papers, one of which examined petal distri-
bution in composite flowers and the relation to the
Fibonacci sequence, an exercise that required
counting the petals on more than 6,000 flowers (2). The
experience and mentoring he received encouraged
Chakravarti.

Chakravarti was deeply influenced by his training.
“We were not taught statistics as a tool as it is today.
We were taught statistics as a way of thinking.” True
applications of statistics, he says, “require you to know
the domain to which you apply it,” and it was from that
line of reasoning that Chakravarti sought further
training in human genetics after graduating in 1974. “I
left with a sense of purpose.”

Chakravarti decided to leave India for a doctoral
program in the United States, recalling the advice of
visiting Australian geneticist Robert Kirk, who had told
him that India would continue to be outpaced in the
field. “And this was all before recombinant DNA,
let alone the Human Genome Project,” he says.

Most human genetics programs recruited only
medical degree holders, and Chakravarti wanted the
broad laboratory training that most doctoral epide-
miology programs would not provide.

The relatively new University of Texas Health Science
Center at Houston’s Graduate School of Biomedical
Sciences provided this opportunity. There, Chakravarti

Aravinda Chakravarti. Image courtesy of Sumantra
Chatterjee (New York University School of Medicine,
New York).

Published under the PNAS license.
This is a Profile of a recently elected member of the National Academy of Sciences to accompany the member’s Inaugural Article on page 10636.
Published online May 6, 2019.

10608–10610 | PNAS | May 28, 2019 | vol. 116 | no. 22 www.pnas.org/cgi/doi/10.1073/pnas.1906109116

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studied with population geneticist Masatoshi Nei and
relished the laboratory work. “At that point in time, I was
learning the technical details. We didn’t worry about
jobs or grants, we just did research,” he says. “It was
really just extending my childhood.” During that period,
he also published a cookbook, Not Everything We Eat Is
Curry: A Bengali Guide to Indian Cuisine, and married
biochemist Shukti Chakravarti (3).

Chakravarti’s childhood—but not his passions for
his family and cooking—came to an end with gradu-
ation in 1979 and a short-lived postdoctoral position
at the University of Washington, where he worked on
demographic genetics and large datasets. “It was big
data for those days, with intense computing,” he says.
“You’d laugh at the computers now.” However, the
experience was not quite what Chakravarti wanted.

Getting a Handle on Things
In 1980, Chakravarti took a teaching job at the Univer-
sity of Pittsburgh Graduate School of Public Health. He
was responsible for six courses a year. He initially had
no office or staff, and had to go to the computer center
to enter and analyze data. However, the time proved
fruitful. He worked with preeminent population genet-
icist C. C. Li, a founder of the field, and began a col-
laboration with Haig Kazazian and Stylianos Antonarakis
to understand the molecular diversity of the β-globin
gene cluster in humans, eventually identifying a hotspot
for recombination (4).

Using population genetics to predict the disease
state of individuals intrigued Chakravarti. Since 1978,
when the sickle cell mutation was shown to be asso-
ciated with a noncoding polymorphism in DNA, he
had imagined that the association, called linkage
disequilibrium, could be used to map mutations in
reverse. Outliers, alleles that associate at rates higher
than random assortment, could predict disease and
provide the foundation for his work.

By the late 1980s, Chakravarti wanted to apply the
concept of linkage disequilibrium to a disease whose
genetic underpinnings were unknown. “The genes
cloned at the time had a lesion, deletion, or transloca-
tion at the disease locus, which was used as a handle for
getting at the gene.” Cystic fibrosis had no such han-
dles, but Chakravarti was convinced its high prevalence
in the population was indicative of selection, and thus
the key to the problem. “There’s no way you could have
selection without inducing strong linkage disequilib-
rium.” Chakravarti’s hunch was correct, and before
long, his team published the positional location of
CFTR using this principle (5). “That was the first success
in mapping a common disease allele in a general—not
isolated—population,” says Chakravarti.

In addition, the marker maps created to solve the
cystic fibrosis problem and detect the alleles’ mutual
association (i.e., haplotypes) prompted Chakravarti’s
role in the eventual creation of the International Hap-
Map Project, where he served on the steering com-
mittee from 2002 to 2007, as well as his eventual
contributions to the 1000 Genomes Project (6). Both are
projects that aim to catalog human genetic variation for
phenotypic mapping. For Chakravarti and other human

geneticists, it is genetic variation and its association that
ironically provide both the power to map and the po-
tential to confound causal and irrelevant factors.

Meeting Serendipity
To sort through the genetic noise, Chakravarti has relied
on a de facto model disease. Chance led Chakravarti to
begin studying Hirschsprung disease in 1988 after lis-
tening to an account of a debilitating congenital disor-
der that prevents proper innervation of the intestinal
tract. What he heard did not sound like either a multi-
factorial or Mendelian disease, and he thought, “Maybe
what I should do is to devise methods for studying such
complicated non-Mendelian disorders.”

The challenges would be vast. “We didn’t know at
what resolution we needed to develop markers,” he
says. “It wasn’t like you could look them up.” When
David Kupfer, chair of the psychiatry department,
asked Chakravarti to study mood disorders instead,
Chakravarti agreed to consult if Kupfer provided lab-
oratory space for his Hirschsprung disease studies.
“He gave me the gift of a career.”

Chakravarti learned how to do family studies, be-
ginning with Old Order Mennonite populations, and he
now feels a kinship with what he refers to as “his”
families. “These are not families that we simply get data
on. We communicate with them, and when they
have problems, I’m not an MD, but I make a point of
connecting them with experts.”

In 1993, his work mapped one of the major genes,
RET, for Hirschsprung disease, which encodes a tyro-
sine kinase receptor (7). Much of the overall genetic
variation in RET was not in the coding areas, but it was
not until years later that these variations would be
revealed in its enhancers, noncoding genetic elements
that affect the expression of RET (8).

Today, after 28 years of research and at least
24 genes so far implicated in its cause, the heritability of
Hirschsprung disease is mostly, but not fully, explained,
according to Chakravarti. “We are using these lessons
for more complicated disorders,” he says. “It never

Network of regulatory genes underlying Hirschsprung disease. Such networks
are thought to underlie other complex traits and disorders. Image courtesy of
Aravinda Chakravarti and Sumantra Chatterjee (New York University School of
Medicine, New York).

Davis PNAS | May 28, 2019 | vol. 116 | no. 22 | 10609



ceases to amaze me what a single model system can
teach you. I believe that we have to first choose systems
that can really illuminate features that we want to learn.
Databases and knowledge are not the same thing.”

While he was director of the Center for Complex
Disease Genomics at Johns Hopkins University in 2015,
Chakravarti identified a rare genetic cause of autism
by studying families in which females were severely
affected (9). In addition to these two congenital con-
ditions, he focused on two genetically complex adult-
onset conditions: hypertension, having identified more
than 150 genetic contributors over the years (10), and
sudden cardiac death (11). The heart rhythm’s QT in-
terval is physiologically determined, and intervals that
are too short or too long can lead to problems. In his

Inaugural Article, Chakravarti focused on the genetic
control of this physiological process, determining that
eight of the 13 cis-regulatory gene variants identified
by a genome-wide association study are causal, im-
plying that they affect regulation of SCN5A (1).

Throughout his career, Chakravarti has held posi-
tions in departments as diverse as anthropology, bio-
statistics, and psychiatry. However, there are two
scientific disciplines that he considers of particular rel-
evance to human societies. “Socially, I am a complete
egalitarian, but of all the biological sciences, even
today, I think two of the greatest of public interest
are genetics and neuroscience,” he says noting that
they come with high public relevance and ethical
responsibilities.

1 Kapoor A, et al. (2019) Multiple SCN5A variant enhancers modulate its cardiac gene expression and the QT interval. Proc Natl Acad
Sci USA 116:10636–10645.

2 Majumder PP, Chakravarti A (1976) Variation in the ray and disk florets in four species of compositae. Fibonacci Quart 14:97–100.
3 Chakravarti A, Morizot DC (1978) Not Everything We Eat Is Curry: A Bengali Guide to Indian Cuisine (Harold House, Houston).
4 Chakravarti A, et al. (1984) Nonuniform recombination within the human beta-globin gene cluster. Am J Hum Genet 36:1239–1258.
5 Kerem B, et al. (1989) Identification of the cystic fibrosis gene: Genetic analysis. Science 245:1073–1080.
6 Abecasis GR, et al.; 1000 Genomes Project Consortium (2012) An integrated map of genetic variation from 1,092 human genomes.
Nature 491:56–65.

7 Angrist M, et al. (1995) Mutation analysis of the RET receptor tyrosine kinase in Hirschsprung disease. Hum Mol Genet 4:821–830.
8 Emison ES, et al. (2005) A common sex-dependent mutation in a RET enhancer underlies Hirschsprung disease risk. Nature 434:857–
863.

9 Turner TN, et al. (2015) Loss of δ-catenin function in severe autism. Nature 520:51–56.
10 Ehret GB, et al.; CHARGE-EchoGen consortium; CHARGE-HF consortium; Wellcome Trust Case Control Consortium (2016) The

genetics of blood pressure regulation and its target organs from association studies in 342,415 individuals. Nat Genet 48:1171–1184.
11 Arking DE, et al. (2006) A common genetic variant in the NOS1 regulator NOS1AP modulates cardiac repolarization. Nature Genet

38:644–651.

10610 | www.pnas.org/cgi/doi/10.1073/pnas.1906109116 Davis

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