Human genetic clustering: Difference between revisions

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'''Human genetic clustering''' refers to patterns of relative genetic similarity among human individuals and populations, as well as the wide range of scientific and statistical methods used to study this aspect of [[human genetic variation]].

Clustering studies are thought to be valuable for characterizing the general structure of genetic variation among human populations, to contribute to the study of ancestral origins, evolutionary history, and precision medicine. Since the mapping of the human genome, and with the availability of increasingly powerful analytic tools, [[Cluster analysis|cluster analyses]] have revealed a range of ancestral and migratory trends among human populations and individuals.<ref name=":02">{{Cite journal|last1=Novembre|first1=John|last2=Ramachandran|first2=Sohini|date=2011-09-22|title=Perspectives on Human Population Structure at the Cusp of the Sequencing Era|url=http://dx.doi.org/10.1146/annurev-genom-090810-183123|journal=Annual Review of Genomics and Human Genetics|volume=12|issue=1|pages=245–274|doi=10.1146/annurev-genom-090810-183123|pmid=21801023|issn=1527-8204|url-access=subscription}}</ref> Human genetic clusters tend to be organized by geographic ancestry, with divisions between clusters aligning largely with geographic barriers such as oceans or mountain ranges.<ref name=":32">{{Cite journal|last1=Maglo|first1=Koffi N.|last2=Mersha|first2=Tesfaye B.|last3=Martin|first3=Lisa J.|date=2016-02-17|title=Population Genomics and the Statistical Values of Race: An Interdisciplinary Perspective on the Biological Classification of Human Populations and Implications for Clinical Genetic Epidemiological Research|journal=Frontiers in Genetics|volume=7|page=22|doi=10.3389/fgene.2016.00022|pmid=26925096|pmc=4756148|issn=1664-8021|doi-access=free}}</ref><ref name=":92">{{Cite book|date=2012-10-29|editor-last=Goodman|editor-first=Alan H.|editor2-last=Moses|editor2-first=Yolanda T.|editor3-last=Jones|editor3-first=Joseph L.|title=Race|url=http://dx.doi.org/10.1002/9781118233023|doi=10.1002/9781118233023|isbn=9781118233023}}</ref> Clustering studies have been applied to global populations,<ref name=":102">{{Cite journal|last=Rosenberg|first=N. A.|date=2002-12-20|title=Genetic Structure of Human Populations|url=http://dx.doi.org/10.1126/science.1078311|journal=Science|volume=298|issue=5602|pages=2381–2385|doi=10.1126/science.1078311|pmid=12493913|bibcode=2002Sci...298.2381R|s2cid=8127224|issn=0036-8075|url-access=subscription}}</ref> as well as to population subsets like post-colonial North America.<ref name=":112">{{Cite journal|last1=Han|first1=Eunjung|last2=Carbonetto|first2=Peter|last3=Curtis|first3=Ross E.|last4=Wang|first4=Yong|last5=Granka|first5=Julie M.|last6=Byrnes|first6=Jake|last7=Noto|first7=Keith|last8=Kermany|first8=Amir R.|last9=Myres|first9=Natalie M.|last10=Barber|first10=Mathew J.|last11=Rand|first11=Kristin A.|date=2017-02-07|title=Clustering of 770,000 genomes reveals post-colonial population structure of North America|journal=Nature Communications|language=en|volume=8|issue=1|pages=14238|doi=10.1038/ncomms14238|pmid=28169989|pmc=5309710|bibcode=2017NatCo...814238H|issn=2041-1723|doi-access=free}}</ref><ref name=":122">{{Cite journal|last1=Jordan|first1=I. King|last2=Rishishwar|first2=Lavanya|last3=Conley|first3=Andrew B.|date=September 2019|title=Native American admixture recapitulates population-specific migration and settlement of the continental United States|journal=PLOS Genetics|volume=15|issue=9|pages=e1008225|doi=10.1371/journal.pgen.1008225|issn=1553-7404|pmc=6756731|pmid=31545791 |doi-access=free }}</ref> Notably, the practice of defining clusters among modern human populations is largely arbitrary and variable due to the continuous nature of human genotypes; although individual genetic markers can be used to produce smaller groups, there are no models that produce completely distinct subgroups when larger numbers of genetic markers are used.<ref name=":32" /><ref name=":52">{{Cite journal|last1=Bamshad|first1=Michael J.|last2=Olson|first2=Steve E.|date=December 2003|title=Does Race Exist?|url=http://dx.doi.org/10.1038/scientificamerican1203-78|journal=Scientific American|volume=289|issue=6|pages=78–85|doi=10.1038/scientificamerican1203-78|pmid=14631734|bibcode=2003SciAm.289f..78B|issn=0036-8733|url-access=subscription}}</ref><ref name=":22">{{Cite journal|last=Kalinowski|first=S T|date=2010-08-04|title=The computer program STRUCTURE does not reliably identify the main genetic clusters within species: simulations and implications for human population structure|journal=Heredity|volume=106|issue=4|pages=625–632|doi=10.1038/hdy.2010.95|pmid=20683484|pmc=3183908|issn=0018-067X|doi-access=free}}</ref>

Many studies of human genetic clustering have been implicated in discussions of [[Race (human categorization)|race]], [[Ethnic group|ethnicity]], and [[scientific racism]], as some have controversially suggested that genetically derived clusters may be understood as proof of genetically determined races.<ref name=":42">{{Cite journal|last1=Jorde|first1=Lynn B|last2=Wooding|first2=Stephen P|date=2004-10-26|title=Genetic variation, classification and 'race'|journal=Nature Genetics|volume=36|issue=S11|pages=S28–S33|doi=10.1038/ng1435|pmid=15508000|issn=1061-4036|doi-access=free}}</ref><ref>{{Cite book|last=Marks|first=Jonathan|url=httphttps://worldcat.org/oclc/1037867598|title=Is science racist?|date=27 February 2017|publisher=John Wiley & Sons |isbn=978-0-7456-8925-8|oclc=1037867598}}</ref> Although cluster analyses invariably organize humans (or groups of humans) into subgroups, since the work of evolutionary biologists such as [[Richard Lewontin]], [[Luigi Luca Cavalli-Sforza|Luigi Cavalli-Sforza]], and [[Marcus Feldman]] in the 1970s there is virtually no debate within human genetics that any of these genetic clusters can be attributed to races, nor does knowing any individual's skin tone or continent of origin constitute a meaningful prediction of specific alleles.<ref name=":0">{{Cite web |date=2021-11-19 |title=What Can Genetic Testing Tell You About ‘Race’? |url=https://magazine.scienceforthepeople.org/lewontin-special-issue/genetics-of-race-gswg/ |access-date=2025-02-26 |website=Science for the People Magazine |language=en-US}}</ref> And, because there is such a small fraction of genetic variation between human genotypes overall, genetic clustering approaches are highly dependent on the sampled data, genetic markers, and statistical methods applied to their construction. It has also been repeatedly demonstrated by various methodologies that the five races ([[caucasoid]], [[mongoloid]], [[negroid]], [[Red race|American]] or "red", and [[Malay race|Malay]]) historically purported by scientific racism do not comport with population substructures derivable from any modern genomic datasets.<ref>{{Cite journal |last=Auton |first=Adam |last2=Abecasis |first2=Gonçalo R. |last3=Altshuler |first3=David M. |last4=Durbin |first4=Richard M. |last5=Abecasis |first5=Gonçalo R. |last6=Bentley |first6=David R. |last7=Chakravarti |first7=Aravinda |last8=Clark |first8=Andrew G. |last9=Donnelly |first9=Peter |last10=Eichler |first10=Evan E. |last11=Flicek |first11=Paul |last12=Gabriel |first12=Stacey B. |last13=Gibbs |first13=Richard A. |last14=Green |first14=Eric D. |last15=Hurles |first15=Matthew E. |date=October 2015 |title=A global reference for human genetic variation |url=https://www.nature.com/articles/nature15393 |journal=Nature |language=en |volume=526 |issue=7571 |pages=68–74 |doi=10.1038/nature15393 |issn=1476-4687|hdl=11693/38161 |hdl-access=free |pmc=4750478 }}</ref> Rather, the evidence for [[Cline (biology)|clinal]] patterns of human genetic variation overwhelms that pointing towards distinct groups defined by [[Human skin color|skin pigmentation]] or [[Phrenology|skull shape]],<ref name=":0" />, and arbitrarily invoking five population clusters in an attempt to test the genomic validity of scientific racism instead yields three "races" within Africa, one encompassing most of Europe and mainland Asia, and one encompassing Australia, the Americas, and the Pacific Islands.<ref>{{Cite journal |last=Lala |first=Kevin N. |last2=Feldman |first2=Marcus W. |date=2024-11-26 |title=Genes, culture, and scientific racism |url=https://www.pnas.org/doi/10.1073/pnas.2322874121 |journal=Proceedings of the National Academy of Sciences |volume=121 |issue=48 |pages=e2322874121 |doi=10.1073/pnas.2322874121 |pmc=11621800 |pmid=39556747}}</ref>

== Genetic clustering algorithms and methods ==

A wide range of methods have been developed to assess the structure of human populations with the use of genetic data. Early studies of within and between-group genetic variation used physical phenotypes and blood groups, with modern genetic studies using genetic markers such as [[Alu element|Alu sequences]], [[Microsatellite|short tandem repeat polymorphisms]], and [[Single-nucleotide polymorphism|single nucleotide polymorphisms]] (SNPs), among others.<ref>{{Cite journal|last1=Bamshad|first1=Michael|last2=Wooding|first2=Stephen|last3=Salisbury|first3=Benjamin A.|last4=Stephens|first4=J. Claiborne|date=August 2004|title=Deconstructing the relationship between genetics and race|url=http://dx.doi.org/10.1038/nrg1401|journal=Nature Reviews Genetics|volume=5|issue=8|pages=598–609|doi=10.1038/nrg1401|pmid=15266342|s2cid=12378279|issn=1471-0056|url-access=subscription}}</ref> Models for genetic clustering also vary by algorithms and programs used to process the data. Most sophisticated methods for determining clusters can be categorized as '''model-based clustering methods''' (such as the algorithm STRUCTURE<ref name=":132">{{Cite journal|last1=Pritchard|first1=Jonathan K|last2=Stephens|first2=Matthew|last3=Donnelly|first3=Peter|date=2000-06-01|title=Inference of Population Structure Using Multilocus Genotype Data|journal=Genetics|volume=155|issue=2|pages=945–959|doi=10.1093/genetics/155.2.945|pmid=10835412|pmc=1461096|issn=1943-2631|doi-access=free}}</ref>) or '''multidimensional summaries''' (typically through principal component analysis).<ref name=":02" /><ref name=":14">{{Cite journal|last1=Lawson|first1=Daniel John|last2=Falush|first2=Daniel|date=2012-09-22|title=Population Identification Using Genetic Data|journal=Annual Review of Genomics and Human Genetics|volume=13|issue=1|pages=337–361|doi=10.1146/annurev-genom-082410-101510|pmid=22703172|issn=1527-8204|doi-access=free}}</ref> By processing a large number of SNPs (or other genetic marker data) in different ways, both approaches to genetic clustering tend to converge on similar patterns by identifying similarities among SNPs and/or [[haplotype]] tracts to reveal ancestral genetic similarities.<ref name=":14" />

=== [[Model-based clustering]] ===

[[File:Rosenberg_1048people_993markers.jpg|thumb|Human population structure has been inferred from multilocus DNA sequence data (Rosenberg et al. 2002, 2005). Individuals from 52 populations were examined at 993 DNA markers. This data was used to partition individuals into K = 2, 3, 4, 5, or 6 gene clusters. In this figure, the average fractional membership of individuals from each population is represented by horizontal bars partitioned into K colored segments.]]

Common [[model-based clustering]] algorithms include STRUCTURE, ADMIXTURE, and HAPMIX. These algorithms operate by finding the best fit for genetic data among an arbitrary or mathematically derived number of clusters, such that differences within clusters are minimized and differences between clusters are maximized. This clustering method is also referred to as "[[Genetic admixture|admixture]] inference," as individual genomes (or individuals within populations) can be characterized by the proportions of [[allele]]s linked to each cluster.<ref name=":02" /> In other words, algorithms like STRUCTURE generate results that assume the existence of discrete ancestral populations, operationalized through unique genetic markers, which have combined over time to form the admixed populations of the modern day.

=== Multidimensional summary statistics ===

[[File:Whole-genome based PCA and clustering of worlds ethnic groups.png|thumb|upright=1.4|A 2023 [[Whole genome sequencing|whole-genome study]] of modern-day ethnic groups in the world identified 14 genomic clusters, which do not exactly align with current categorizations of race or ethnicity. The study also found that "99.8% of whole genome is identical between two individuals". Left image shows [[Cluster analysis|clustering]] following [[principal component analysis]] with [[Three-dimensional space|three dimensions]]. Top right image shows geographical locations where samples were collected.<ref name=Kim_Choi_Kim_2023>{{cite journal |doi=10.1038/s41598-023-32325-w |title=On whole-genome demography of world's ethnic groups and individual genomic identity |date=2023 |last1=Kim |first1=Byung-Ju |last2=Choi |first2=Jaejin |last3=Kim |first3=Sung-Hou |journal=Scientific Reports |volume=13 |issue=1 |page=6316 |pmid=37072456 |pmc=10113208 |bibcode=2023NatSR..13.6316K }}</ref>]]

Where model-based clustering characterizes populations using proportions of presupposed ancestral clusters, multidimensional summary statistics characterize populations on a continuous spectrum. The most common multidimensional statistical method used for genetic clustering is [[principal component analysis]] (PCA), which plots individuals by two or more axes (their "principal components") that represent aggregations of genetic markers that account for the highest variance. Clusters can then be identified by visually assessing the distribution of data; with larger samples of human genotypes, data tends to cluster in distinct groups as well as admixed positions between groups.<ref name=":02" /><ref name=":14" />

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Some scholars{{who|date=August 2021}} have challenged the idea that race can be inferred by genetic clusters, drawing distinctions between arbitrarily assigned genetic clusters, ancestry, and race. One recurring caution against thinking of human populations in terms of clusters is the notion that genotypic variation and traits are distributed evenly between populations, along gradual [[Cline (biology)|clines]] rather than along discrete population boundaries; so although genetic similarities are usually organized geographically, their underlying populations have never been completely separated from one another. Due to migration, gene flow, and baseline homogeneity, features between groups are extensively overlapping and intermixed.<ref name=":32" /><ref name=":42" /> Moreover, genetic clusters do not typically match socially defined racial groups; many commonly understood races may not be sorted into the same genetic cluster, and many genetic clusters are made up of individuals who would have distinct racial identities.<ref name=":52" /> In general, clusters may most simply be understood as products of the methods used to sample and analyze genetic data; not without meaning for understanding ancestry and genetic characteristics, but inadequate to fully explaining the concept of race, which is more often described in terms of social and cultural forces.

In the related context of [[personalized medicine]], race is currently listed as a [[risk factor]] for a wide range of medical conditions with genetic and non-genetic causes. Questions have emerged regarding whether or not genetic clusters support the idea of race as a valid construct to apply to medical research and treatment of disease, because there are many diseases that correspond with specific genetic markers and/or with specific populations, as seen with [[Tay–Sachs disease|Tay-Sachs disease]] or [[sickle cell disease]].<ref name=":92" /><ref name=":63">{{Cite book|last1=Koenig|first1=Barbara A. Lee|first2=Sandra|last2=Soo-Jin|last3=Richardson|first3=Sarah S.|author-link3=Sarah S. Richardson|url=httphttps://worldcat.org/oclc/468194495|title=Revisiting race in a genomic age|date=2008|publisher=Rutgers University Press|isbn=978-0-8135-4323-9|oclc=468194495}}</ref> Researchers are careful to emphasize that ancestry—revealed in part through cluster analyses—plays an important role in understanding risk of disease. But racial or ethnic identity does not perfectly align with genetic ancestry, and so race and ethnicity do not reveal enough information to make a medical diagnosis.<ref name=":63" /> Race as a variable in medicine is more likely to reflect social factors, where ancestry information is more likely to be meaningful when considering genetic ancestry.<ref name=":32" /><ref name=":63" />

== References ==