Showing posts with label Europe. Show all posts
Showing posts with label Europe. Show all posts

Wednesday, September 23, 2015

Pain: OPRM1 & The Ancestral Contribution [Review]

A paper by Soto & Catanesi assessing genetic variation in the μ (mu) opioid receptor gene (OPRM1) was published in May 2015. OPRM1 contributes to the structure of the μ opioid receptor (MOR), one of three major opioid receptor types which broadly contribute to pain sensation, addiction, ion influx into cells and a host of other functions [1]. 

WHO Pain Ladder (courtesy of paineurope.com)
Opioid receptors are of interest to medical researchers due to the varying specificity of receptor agonism (activation) by conventional treatments (e.g. tramadol has a higher affinity to MORs than others [2]). Additionally, opioid receptor antagonists are widely used in pain management (as directed by the World Health Organisation's classic "pain management ladder", figure opposite [3]). As such, understanding the structure of opioid receptor characteristics between individuals could theoretically fine-tune the ideal pharmaceutical agents to be used in specific situations, such as in palliative or acute care, as well as narcotic or surgical rehabilitation (in effect stratified or personalised medicine).

Although the paper indicates contradiction in our current data regarding the most studied SNP to date (rs1799971, linked to the A118G polymorphism), others residing within or near OPRM1 are postulated to have an effect on MOR function.

OPRM1 from a population genetics perspective is of interest through the observation in numerous older studies (listed within paper) that show differing A118G polymorphism frequencies across various world populations. The authors extended these findings by including the HapMap world database with their own Argentinian samples to determine whether OPRM1 SNP variants correlated with ancestral background. Establishing the polymorphic frequency among Argentinians appears to be a secondary aim here.

The authors of this paper concluded that Sub-Saharan African, West and East Eurasian ancestral status coincides with OPRM1 polymorphism status in the several SNPs examined (through the use of Fst and AMOVA). However, they noted that no such clustering was observed between West Eurasians (Europeans) and American populations (mixed Argentinian and Mexican samples). This was taken to indicate extensive gene flow from European colonists had made a massive contribution to the polymorphic status at this gene. 

Another possibility not highlighted in the paper is that the native Amerindian population of pre-colonial America had similar OPRM1 polymorphic status as modern West Eurasians. In light of the recent findings supporting sizeable mutual prehistoric ancestry between these two populations through a conceptual "Ancestral North Eurasian" (ANE) component (Raghavan et al., see below) [4], the OPRM1 congruity between Amerind-European mixed modern Americans and Europeans could partially be attributed to the proposed ANE-containing migratory events. [4] 

Estimated Shared Drift Heat Map with MA1 (Raghavan et al.)


Overall, Soto & Catanesi provide us with a good summary of the population structure that can be directly observed through OPRM1 gene polymorphism variation and support earlier work indicating a correlation with ancestry. It would have furnished their discussion better had some exploration of recent developments in archaeogenetics been undertaken. Their assertion of complete OPRM1 SNP status replacement among Amerind-European admixed American individuals is of course possible, but no evidence is provided that categorically dismisses commonality between Europeans and Amerindians on this genomic region as at least partially responsible for the observation.

Human population genetic structure detected by pain-related mu opioid receptor gene polymorphisms.
López Soto EJ, Catanesi CI. Genet Mol Biol. 2015 May;38(2):152-5. doi: 10.1590/S1415-4757382220140299. Epub 2015 May 1.
"Several single nucleotide polymorphisms (SNPs) in the Mu Opioid Receptor gene (OPRM1) have been identified and associated with a wide variety of clinical phenotypes related both to pain sensitivity and analgesic requirements. The A118G and other potentially functional OPRM1 SNPs show significant differences in their allele distributions among populations. However, they have not been properly addressed in a population genetic analysis. Population stratification could lead to erroneous conclusions when they are not taken into account in association studies. The aim of our study was to analyze OPRM1 SNP variability by comparing population samples of the International Hap Map database and to analyze a new population sample from the city of Corrientes, Argentina. The results confirm that OPRM1 SNP variability differs among human populations and displays a clear ancestry genetic structure, with three population clusters: Africa, Asia, and Europe-America."


References
1. Feng Y, He X, Yang Y, Chao D, Lazarus LH, Xia Y. Current research on opioid receptor function. Curr Drug Targets. 2012 Feb;13(2):230-46.

2. Dayer P, Desmeules J, Collart L. [Pharmacology of tramadol]. Drugs. 1997;53 Suppl 2:18-24. [Article in French]

3. WHO | WHO's cancer pain ladder for adults. [Last Retrieved 22/09/2015]: http://www.who.int/cancer/palliative/painladder/en/ 

4. Raghavan M, Skoglund P, Graf KE, Metspalu M, Albrechtsen A. Upper Palaeolithic Siberian genome reveals dual ancestry of Native Americans. Nature. 2014 Jan 2;505(7481):87-91. doi: 10.1038/nature12736. Epub 2013 Nov 20.

Friday, September 5, 2014

Worldwide Population Y-DNA Collated (Xu et al.) [Review]

Approximately one week has passed since a new paper by Xu et al. was indexed by PubMed and made available online ahead of printing:

"The Y chromosome is one of the best genetic materials to explore the evolutionary history of human populations. Global analyses of Y chromosomal short tandem repeats (STRs) data can reveal very interesting world population structures and histories. However, previous Y-STR works tended to focus on small geographical ranges or only included limited sample sizes. In this study, we have investigated population structure and demographic history using 17 Y chromosomal STRs data of 979 males from 44 worldwide populations. The largest genetic distances have been observed between pairs of African and non-African populations. American populations with the lowest genetic diversities also showed large genetic distances and coancestry coefficients with other populations, whereas Eurasian populations displayed close genetic affinities. African populations tend to have the oldest time to the most recent common ancestors (TMRCAs), the largest effective population sizes and the earliest expansion times, whereas the American, Siberian, Melanesian, and isolated Atayal populations have the most recent TMRCAs and expansion times, and the smallest effective population sizes. This clear geographic pattern is well consistent with serial founder model for the origin of populations outside Africa. The Y-STR dataset presented here provides the most detailed view of worldwide population structure and human male demographic history, and additionally will be of great benefit to future forensic applications and population genetic studies."

This paper showcases a staggering 979 distinct Y-DNA 17 STR haplotypes across 44 distinct populations from across the world. These haplotypes are soon to be uploaded to the Y-STR Haplotype Resource Database (YHRD). The authors have made all the haplotypes, together with a slew of additional information, publicly available independent of the official article (raw haplotypes, Y-DNA haplogroup predictions).

In this entry, the collated results of all populations are reviewed, together with cursory inferences provided with the intention of aiding interpreting them.


Method
All 979 haplotypes were retrieved through the above link. Each population dataset was run through Vadim Urasin's YPredictor (v1.5.0). A 70% prediction strength threshold was implemented. All nomenclature were reduced to the haplogroup level to avoid confusion for future readers should these change in time. These haplotypes formed the collated population results.


Results
877 haplotype predictions met the 70% threshold established. Without having access to the original study, it is apparent that the authors also used Urasin's YPredictor, given the identical predictions.

The collated population results have been organised by the location of sampling by continent or region and can be found in the Data Sink. Direct links to each section accompanied by the list of populations sampled are listed below for the reader's convenience with a brief runthrough of some interesting findings under each.

1. Europe Adygei (Russia), Chuvash (Russia), Danes (Denmark), Finns (Finland), Hungarians (Hungary), Irish (Ireland), Khanty (Russia), Komi (Russia), Russians (Archangelsk), Russians (Vologda), Yakut (Russia)

The Adygei present as expected; they are predominantly G-P15 and J-L26 with various subclades of haplogroup R. Various subclades of haplogroups N and R define the Chuvash, with an additional appearance by J-L26 and Q-MEH2. Ethnic Russian populations appear to have their own regionalised diversity on the backdrop of being predominantly R-M198 and downstream subclades (particularly R-M458). The Irish are predominantly (~81%) R-M269, although the presence of a single man with H-M82 is surprising. Finally, the Yakut too belong overwhelmingly to haplogroup N (~78%) with a single man being predicted as I-P37.2.

2. Middle-East Druze (Israel), Samaritans (Israel), Yemenite Jews (Yemen)

The Druze are one of the better-sampled populations in this study, where they are mostly represented by various subclades of haplogroups E and G, together with R-M269 and T-L162. The Samaritans are defined (in order of decreasing frequency) exclusively by J-L26, J-P58 and E-V22. Finally, the Yemenite Jews present with a similar (though more restricted) spectrum as the Druze with some differences in frequency.

3. East Asia Ami (Taiwan), Atayal (Taiwan), Cambodians (Cambodia), Chinese (USA), Chinese (Taiwan), Hakka (Taiwan), Japanese (USA), Koreans (S. Korea), Laotians (Laos)

The Ami are unsurprisingly defined mostly by downstream subclades of haplogroup O, although there does appear to be an I-M223 and L-M317 among them. The Atayal, also of Taiwan, are exclusively O-MSY2.2. The Cambodians appear to have even more lineages which are typically expected further west. The Japanese boast the highest frequency of D-M55 out of all the populations sampled (21.1%). The Korean results contrast with this through the presence of men with N*-LLY22g(xM128,P43,Tat) and Q-MEH2. The Laotians appear to have one man with DE*-M1, although this will require SNP testing to definitively confirm.

4. Africa Ashkenazi Jews (S. Africa), Biaka Pygmies (CAR), Chagga's (Tanzania), Ethiopian Jews (Ethiopia), Hausa (Nigeria), Ibo (Nigeria), Masai (Tanzania-Kenya), Mbuti Pgymies (Congo R.), Sandawe (Tanzania), Yoruba (Nigeria)

The Ashkenazi Jews of South Africa appear to have a Y-DNA spectrum that is completely typical of Southwest Asians (please compare with the Druze). The Bagandu are largely defined by subclades of haplogroups B and E. Tanzanians here are completely haplogroup E and T. The presence of G-M15, J-L26 and R-M269 among the Hausa is surprising and may be attributed to a colonial European presence or some other forms of interaction.  The Sandawe have some rather unusual results given their geographical position (I-P37.2 and Q-MEH2), raising the possibility these haplotypes were predicted incorrectly.

5. Australasia Micronesians (Micronesia), Nasioi Melanesians (Solomon Islands)

Both the Micronesians and Melanesians have an unusually diverse spectrum. It is difficult to ascertain whether the parahaplogroups shown are genuine or, as described above, a result of incorrect predictions. A recent paper revealing the presence of newly discovered offshoots from haplogroup K in Southeast Asia [1] raise the possibility some of these may be genuine.

6. Americas Karitiana (Brazil), African Americans (USA), European Americans (USA), Maya (Mexico), Pima (USA), Rondonian Surui (Brazil), Ticuna (Brazil)

The Karitiana are predominantly Q-MEH2 but appear to have some non-American admixture through E-U175. African Americans are represented as an approximately 4:6 mix of R-M269 against various haplogroup E subclades. The Maya population, like the Karitiana, are Q-MEH2 with additional markers from outside the Americas, as are the Pima. The trend continues with the Quechua people, although C-M217 and T-L162 make their first appearance here. Finally, the Rondonian Surui and Ticuna are completely Q-MEH2.


Criticisms
There are at least two areas of the authors' methodology which are deemed to be drawbacks and prevent this study from being exceptionally informative.

Firstly, the authors evidently used the YFiler sampling array to complete this investigation. In an era where commercial testees can enjoy upwards of 111 Y-STR's, the long-term usefulness of this paper's extensive worldwide sampling is cut short. Another recent paper presenting Y-STR's worldwide has done so using 23 rather than just 17. [2]

My comments are more critical of the authors' sampling strategy. More data is never strictly a burden in the world of population genetics, but the informativeness of groups such as "European Americans", "Irish" and Chinese born in the USA is questionable. For instance, these groups are already richly represented, be it in the current literature or FTDNA Project groups. The apparent issue with these samples would have been rectified if they were simply obtained from a single area, providing regional specificity which may prove useful in better establishing genetic variation within Ireland, for example.

Finally, the haplotypes could have also received a "backbone" SNP test each to definitively place them within the current phylogeny. The drawbacks of STR-alone testing became readily apparent with some of the African samples. I can only speculate it is the highly divergent nature of certain uniquely African haplotypes from Eurasian ones which produced these spurious results.


On Mutation Rates (Quick Discussion)
In this study, both BATWING and the average squared distance (ASD) method were used. Within each, four different mutation rates were implemented. On initial inspection these appear to vary wildly. However, on closer examination, it appears all the BATWING most recent common ancestor (MRCA) calculated ages are approximately twice as old as those generated by the ASD method. Even within each technique there is substantial variation; the evolutionary rate appears approximately three times greater than the others. Furthermore, these "other" mutation rates do tend to congregate around a common similar value (e.g. through BATWING, the calculated global age of their Y-DNA R-M198 haplotypes was 5.5k, 6.1k and 6.2kya), which would intuitively suggest the "actual" value lies somewhere within these either through BATWING or ASD. The discrepancy here cannot be overstated and calls into question why some researchers are still utilising a "blanket" mutation rate across several loci which are shown to have significantly different tendencies to mutate (colloquially described as "slow", "medium" and "fast" mutators). I am uncertain whether the authors are in fact doing this, but the implications of this are apparent, as they prevent rational "fitting" of these numbers into candidate prehistoric narratives from happening. This entire topic will likely be explored in a future entry.


Conclusion
Although at least three drawbacks (four including the MRCA calculations) are identified here, this study provides researchers worldwide with a plethora of data from populations that are either poorly represented in the current literature or have been entirely absent until present. The majority of the results outline the wide Y-chromosomal diversity across the world, whilst also revealing specific trends that have been established in both the current literature and in online discussion boards. An mtDNA counterpart of this paper would be a wonderful addition to see sometime in the near future.

There is a bountiful amount of data to be interpreted with pre-existing ideas/models and compared with prior studies which place a premium on each population's area. I welcome any form of dialogue regarding the results. There, is, for many of us, plenty to elucidate. The conclusion does not end here; I encourage as much further investigation and thought by the readers as the data permits.

[Addendum @ 05/09/2014]: Error regarding Karitiana data. Modified and updated.


Citations
1. Karafet TM, Mendez FL, Sudoyo H, Lansing JS, Hammer MF. Improved phylogenetic resolution and rapid diversification of Y-chromosome haplogroup K-M526 in Southeast Asia. [Last Retrieved 03/09/2014]: http://www.nature.com/ejhg/journal/vaop/ncurrent/full/ejhg2014106a.html 

2. Purps J, Siegert S, Willuweit S, Nagy M, Alves C, Salazar R et al. A global analysis of Y-chromosomal haplotype diversity for 23 STR loci. [Last Retrieved 05/09/2014]: http://www.fsigenetics.com/article/S1872-4973%2814%2900084-2/abstract