The geographical distribution of the family-genetic risk score for drug use disorder in Sweden and its co-localization with areas of social deprivation

Kenneth S Kendler; Ali Mansourian; Pengxiang Zhao; Henrik Ohlsson; Kathleen Stewart; Jan Sundquist; Bo Malmberg; Kristina Sundquist

doi:10.1017/S0033291724002745

The geographical distribution of the family-genetic risk score for drug use disorder in Sweden and its co-localization with areas of social deprivation

Psychol Med. 2024 Dec 2;54(15):1-10. doi: 10.1017/S0033291724002745. Online ahead of print.

Authors

Kenneth S Kendler^{1

2}, Ali Mansourian³, Pengxiang Zhao³, Henrik Ohlsson⁴, Kathleen Stewart⁵, Jan Sundquist^{4

6}, Bo Malmberg⁷, Kristina Sundquist^{4

6}

Affiliations

¹ Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA.
² Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA.
³ Department of Physical Geography and Ecosystem Science, Lund University, Malmö, Sweden.
⁴ Center for Primary Health Care Research, Lund University, Malmö, Sweden.
⁵ Center for Geospatial Information System, Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA.
⁶ Department of Family Medicine and Community Health, Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
⁷ Department of Geography of Stockholm University, Stockholm, Sweden.

Abstract

Background: Drug use Disorder (DUD), the risk for which is substantially influenced by both genetic and social factors, is geographically concentrated in high-risk regions. An important step toward understanding this pattern is to examine geographical distributions of the genetic liability to DUD and a key demographic risk factor - social deprivation.

Methods: We calculated the mean family genetic risk score (FGRS) for DUD ((FGRS_DUD) and social deprivation for each of the 5983 areas Demographic Statistical Areas (DeSO) for all of Sweden and used geospatial techniques to analyze and map these factors.

Results: Using 2018 data, substantial spatial heterogeneity was seen in the distribution of the genetic risk for DUD in Sweden as a whole and in its three major urban centers which was confirmed by hot-spot analyses. Across DeSOs, FGRS_DUD and s.d. levels were substantially but imperfectly correlated (r = + 0.63), with more scattering at higher FGRS_DUD and s.d. scores. Joint mapping across DeSOs for FGRS_DUD and s.d. revealed a diversity of patterns across Sweden. The stability of the distributions of FGRS_DUD and s.d. in DeSOs within Sweden over the years 2012-2018 was quite high.

Conclusions: The geographical distribution of the genetic risk to DUD is quite variable in Sweden. DeSO levels of s.d. and FRGS_DUD were substantially correlated but also disassociated in a number of regions. The observed patterns were largely consistent with known trends in the human geography of Sweden. This effort lays the groundwork for further studies of the sources of geographic variation in rates of DUD.

Keywords: Sweden; drug use disorder; genetic risk; geography; social deprivation.