Mar2020_PR.pptx_JNB paper on Hb and association with MetS

Progress Report

1. Updates/Progress on Research Work Vanessa Joy Timoteo TIGP-MM Student March 05 2020

2. Proposed activities/targets: Selection of correct/appropriate variables to be used in UKB analyses GWAS of Hb using UKB data Preparation and submission of Research Project Update Report (UK Biobank) due on 26 March 2020

3. (1) Selection of variables to be used in UKB analyses Inclusion criteria for GWAS of Hb concentration in UKB (1) UK White only and born in UK

4. Ethnic background Parameters All (502,536) Male (229,134) Female (273,402) Ethnic background White 570 (0.11) 326 (0.14) 244 (0.09) British 442,610 (88.23) 202,345 (88.48) 240,265 (88.03) Irish 13,209 (2.63) 6,309 (2.76) 6,900 (2.53) Any other white background 16,336 (3.26) 6,291 (2.75) 10,045 (3.68) * Subtotal 472,725 215,271 257,454 Mixed 49 (0.01) 19 (0.01) 30 (0.01) White and Black Caribbean 620 (0.12) 230 (0.10) 390 (0.14) White and Black African 425 (0.08) 129 (0.06) 296 (0.11) White and Asian 831 (0.17) 348 (0.15) 483 (0.18) Any other mixed background 1,033 (0.21) 379 (0.17) 654 (0.24) Asian or Asian British 43 (0.01) 20 (0.01) 23 (0.01) Indian, Pakistani, Bangladeshi 8,024 (1.61) 4,294 (1.88) 3,184 (1.37) Any other Asian background 1,815 (0.36) 980 (0.43) 835 (0.31) Black or Black British 27 (0.01) 9 (0.00) 18 (0.01) Caribbean, African 7,911 (1.58) 3,356 (1.47) 4,555 (1.67) Any other Black background 123 (0.2) 42 (0.02) 81 (0.03) Chinese 1,574 (0.31) 584 (0.26) 990 (0.36) Other ethnic group 4,559 (0.91) 1,962 (0.86) 2,597 (0.95) Prefer not to answer / Do not know 1,879 (0.37) Missing 898 Caucasian (genetic ethnic grouping) 409,629 (81.51)

5. Genetic ethnic grouping Indicates samples who self-identified as “WHITE BRITISH” according to ‘Ethnic background’ data field and have very similar genetic ancestry based on a principal components analysis of genotypes

6. Genetic ethnic grouping*Ethnic background Genetic ethnic grouping Ethnic background Caucasian Total White British 409,629 (100) 409,629 (100) Irish Any other white background Mixed White and Black Caribbean White and Black African White and Asian Any other mixed background Asian or Asian British Indian, Pakistani, Bangladeshi Any other Asian background Black or Black British Caribbean, African Any other Black background Chinese Other ethnic group Prefer not to answer / Do not know Missing 92,907

7. Ethnic background*Country of birth (UK)

8. (1) Selection of variables to be used in UKB analyses Inclusion criteria for GWAS of Hb concentration in UKB (502,536) (1) UK White only and born in UK (472,573) (2) 37-73 years old

9. Age Age groupings At Recruitment At Assessment/ Data Collection <40 5 (0.00) 5 (0.00) 40-44 45,909 (9.71) 45,909 (9.71) 45-49 59,898 (12.67) 59,895 (12.67) 50-54 70,765 (14.97) 70,766 (14.97) 55-59 86,135 (18.23) 86,131 (18.23) 60-64 117,322 (24.83) 117,325 (24.83) 65-70 92,533 (19.58) 92,536 (19.58) >70 6 (0.00) 6 (0.00) Males Females Age groupings At Recruitment At Assessment/ Data Collection At Recruitment At Assessment/ Data Collection <40 4 (0.00) 4 (0.00) 1 (0.00) 1 (0.00) 40-44 21,069 (9.79) 21,069 (9.79) 24,840 (9.65) 24,840 (9.65) 45-49 26,436 (12.29) 26,436 (12.29) 33,462 (13.00) 33,459 (13.00) 50-54 30,677 (14.26) 30,675 (14.25) 40,088 (15.58) 40,091 (15.58) 55-59 38,001 (17.66) 38,001 (17.66) 48,134 (18.70) 48,130 (18.70) 60-64 53,453 (24.84) 53,455 (24.84) 63,869 (24.81) 63,870 (24.82) 65-70 45,544 (21.16) 45,544 (21.16) 46,989 (18.26) 46,992 (18.26) >70 5 (0.00) 5 (0.00) 1 (0.00) 1 (0.00) Inclusion criteria for GWAS of Hb concentration in UKB (502,536) (1) UK White only and born in UK (472,573) (2) 37-73 years old  40-70 years old

10. Characterization of Hb among Whites of UKB (N=472,573) Al l (450,634) a Male (206,318) b Female (244,316) c Hb, g/ dL 14.19 ± 1.2 ( 0.09 -22.27) 15.00  1.0 ( 0.12 -20.60) 13.51  1.0 ( 0.09 -22.27) *Missing: a 21,939; b 8,871; c 13,068

11. Characterization of Hct among Whites of UKB (N=472,573) Al l (450,634) a Male (206,319) b Female (244,315) c Hct , % 41.11 ± 3.5 (0.05-72.48) 43.30  3.0 (0.05-71.09) 39.27  2.8 (0.05-72.48) *Missing: a 21,939; b 8,870; c 13,069

12. Characterization of Hb by Age Categories (N=472,573) *5-yr age groups Age groupings Missing Hb (g/ dL ) <40 (n=5) -- 15.08 ± 1.18 (13.20 – 16.17) 40-44 (n=43,637) 2,272 14.14 ± 1.34 (0.31 – 20.90) 45-49 (n=57,006) 2,889 14.09 ± 1.34 (0.20 – 20.14) 50-54 (n=67,500) 3,266 14.16 ± 1.24 (0.11 – 19.80) 55-59 (n=82,077) 4,054 14.22 ± 1.18 (0.12 – 20.30 ) 60-64 (n=112,086) 5,239 14.24 ± 1.18 (0.09 – 20.20) 65-70 (n=88,317) 4,219 14.24 ± 1.20 (1.90 – 22.27) >70 (n=6) -- 15.29 ± 1.28 (14.04 – 17.30 )

13. Characterization of Hct by Age Categories (N=472,573) *5-yr age groups Age groupings Missing Hct (%) <40 (n=5) -- 43.14 ± 3.63 (37.70 – 47.07) 40-44 (n=43,637) 2,272 40.90 ± 3.75 (0.09 – 60.20) 45-49 (n=57,006) 2,889 40.76 ± 3.74 (0.18 – 60.77) 50-54 (n=67,499) 3,267 40.98 ± 3.53 (0.05 – 67.90) 55-59 (n=82,078) 4,053 41.16 ± 3.40 (0.05 – 62.70) 60-64 (n=112,086) 5,239 41.26 ± 3.42 (0.06 – 71.09) 65-70 (n=88,317) 4,219 41.31 ± 3.49 (4.74 – 72.48) >70 (n=6) -- 44.27 ± 3.44 (39.21 – 48.70)

14. Detection of Outliers in Hb Concentration (N=472,573) *Scatterplot of Hb vs Hct

15. Detection of Outliers in Hb Concentration (N=472,573) *Scatterplot of Hb vs Hct

16. Characterization of Hb in Women ( N=257,384) *With vs. without menopause

17. Characterization of Hb in Women (N=257,384 ) *With vs. without menopause

18. Sex*Genetic Sex, Sex*Menopause, and Genetic Sex*Menopause (N=257,384)

19. Characterization of Hb Per 5-Yr Age-at-Menopause in Genetic Females (N=249,551) Age-at-Menopause groupings Females with Menopause (n=153,157) Hb, g/ dL <20 16 (0.01) 20-24 106 (0.07) 13.65 ± 1.1 (9.70-15.80) 25-29 469 (0.31) 13.59 ± 1.0 (10.39-16.70) 30-34 1,275 (0.83) 13.54 ± 1.0 (8.70-17.26) 35-39 3872 (2.53) 13.56 ± 1.0 (0.11-17.40) 40-44 12,966 (8.47) 13.57 ± 0.9 (6.01-22.27) 45-49 33,822 (22.08) 13.57 ± 0.9 (6.00-18.77) 50-54 68,907 (44.99) 13.60 ± 0.9 (0.15-20.08) 55-59 20824 (13.60) 13.66 ± 0.9 (0.14-19.29) 60-64 937 (0.61) 13.64 ± 0.9 (9.90-17.10) >65 8 (0.01) 14.04 ± 1.0 (12.70-15.80) Prefer not to answer 281 (0.18) Do not know 9,637 (6.29)

20. Characterization of Hb in Genetic Females (N=249,551) *With vs. without menopause Al l Genetic Female (203,174) a With Menopause (148,277) b Without Menopause (54,897) c Hb, g/ dL 13.50 ± 1.0 ( 0.11 -22.27) 13.60  0.9 ( 0.11 -22.27) 13.24  1.0 ( 0.31 -19.20) *Missing: a 6,738; b 4,880; c 1,858

21. Characterization of Hct in Genetic Females (N=249,551) *With vs. without menopause Al l Genetic Female (203,173) a With Menopause (148,277) b Without Menopause (54,896) c Hct , % 39.23 ± 2.8 ( 0.05 -72.48) 39.50  2.7 ( 0.05 -72.48) 38.50  2.9 ( 0.09 -60.00) *Missing: a 6,739; b 4,880; c 1,859

22. Age Age groupings At Recruitment At Assessment/ Data Collection <40 5 (0.00) 5 (0.00) 40-44 45,909 (9.71) 45,909 (9.71) 45-49 59,898 (12.67) 59,895 (12.67) 50-54 70,765 (14.97) 70,766 (14.97) 55-59 86,135 (18.23) 86,131 (18.23) 60-64 117,322 (24.83) 117,325 (24.83) 65-70 92,533 (19.58) 92,536 (19.58) >70 6 (0.00) 6 (0.00) Males Females Age groupings At Recruitment At Assessment/ Data Collection At Recruitment At Assessment/ Data Collection <40 4 (0.00) 4 (0.00) 1 (0.00) 1 (0.00) 40-44 21,069 (9.79) 21,069 (9.79) 24,840 (9.65) 24,840 (9.65) 45-49 26,436 (12.29) 26,436 (12.29) 33,462 (13.00) 33,459 (13.00) 50-54 30,677 (14.26) 30,675 (14.25) 40,088 (15.58) 40,091 (15.58) 55-59 38,001 (17.66) 38,001 (17.66) 48,134 (18.70) 48,130 (18.70) 60-64 53,453 (24.84) 53,455 (24.84) 63,869 (24.81) 63,870 (24.82) 65-70 45,544 (21.16) 45,544 (21.16) 46,989 (18.26) 46,992 (18.26) >70 5 (0.00) 5 (0.00) 1 (0.00) 1 (0.00) Inclusion criteria for GWAS of Hb concentration in UKB (502,536) (1) UK White only and born in UK (472,573) (2) 37-73 years old  40-70 years old ( 472,562)

23. Inclusion criteria for GWAS of Hb concentration in UKB (502,536) (1) UK White only and born in UK (472,573) ( 2) 37-73 years old  40-70 years old (472,562) Exclusion criteria (3) Pregnant (459,095) (1) Selection of variables to be used in UKB analyses

24. Inclusion criteria for GWAS of Hb concentration in UKB (502,536) (1) UK White only and born in UK (472,573) ( 2) 37-73 years old  40-70 years old (472,562) Exclusion criteria (3) Pregnant (459,095) (1) Selection of variables to be used in UKB analyses *Note that in over 300 cases the genetic sex differs from the self-reported value in Field 31 (Sex).

25. Sex*Genetic Sex and *Genetic Sex*Pregnancy

26. Inclusion criteria for GWAS of Hb concentration in UKB (502,536) (1) UK White only and born in UK (472,573) ( 2) 37-73 years old  40-70 years old (472,562) Exclusion criteria ( 3) Pregnant (459,095) (4) Self-reported cancer/s (420,119) (1) Selection of variables to be used in UKB analyses

27. Parameters All (502,536) Number of self-reported cancers 459,974 (91.7) 1 38,923 (7.76) 2 2,504 (0.50) 3 233 (0.05) > 4 40 (0.01) Types of cancer (top 5) Breast cancer 11,113 (26.65) Basal cell carcinoma 4,064 (9.75) Malignant melanoma 3,477 (8.34) Prostate cancer 3,348 (8.03) Cervical cancer 1,906 (4.57) Number of self-reported cancer/s (Data Field 134)

28. Inclusion criteria for GWAS of Hb concentration in UKB (502,536) (1) UK White only and born in UK (472,573) (2) 37-73 years old  40-70 years old (472,562) Exclusion criteria (3) Pregnant (459,095) (4) Self-reported cancer/s (420,119) (5) Self-reported renal/kidney failures ( 419,461) - Requiring or not requiring dialysis (6) Hereditary/genetic hematological disorder (419,013) - Sickle cell disease or thalassemia (1) Selection of variables to be used in UKB analyses

29. Sickle Cell Disease - a group of inherited red blood cell disorders (abnormal protein in RBCs) - abnormal hemoglobin, called hemoglobin S or sickle hemoglobin - mutations in the beta globin gene that helps make Hb Thalassemias - inherited blood disorders which cause the body to make fewer healthy RBCs and less Hb than normal - patients can have mild or severe anemia - alpha thalassemia trait occurs if one or two of the four genes of alpha globin protein chains are missing - Beta thalassemia occurs if one or both genes of beta globin protein chains are altered Reference : US National Institutes of Health – National Heart, Lung, and Blood Institute

30. Number of self-reported non-cancer illness/ es (Data Field 135) Number of self-reported non-cancers All (502,536) 126,615 (25.24) 1 134,081 (26.73) 2 98,808 (19.70) 3 62,812 (12.52) 4 35,961 (7.17) 5 19,657 (3.92) 6 10,752 (2.14) 7 5,874 (1.17) 8 3,030 (0.60) 9 1,735 (0.35) 10 953 (0.19) 11 558 (0.11) 12 330 (0.07) 13 200 (0.04) 14 109 (0.02) 15 71 (0.01) 16 49 (0.01) 17 26 (0.01) 18 23 (0.00) 19 9 (0.00) 20 5 (0.00) 21-29 16 (0.00) *Missing 862

31. Non-cancer illness/ es , self-reported n_20002_0_0 n_20002_0_1 n_20002_0_2 n_20002_0_3 n_20002_0_4 n_20002_0_5 n_20002_0_6 n_20002_0_7 Renal/urology 1192 28 (0.01) 65 (0.03) 55 (0.04) 37 (0.05) 18 (0.04) 11 (0.05) 8 (0.06) 5 (0.07) 1193 16 (0.00) 83 (0.03) 68 (0.05) 47 (0.06) 28 (0.06) 13 (0.05) 4 (0.03) 2 (0.03) 1194 39 (0.01) 103 (0.04) 91 (0.06) 60 (0.08) 42 (0.10) 22 (0.09) 15 (0.12) 9 (0.13) Hematology/dermatology 1451 145 (0.04) 115 (0.05) 73 (0.05) 50 (0.06) 17 (0.04) 14 (0.06) 7 (0.05) 2 (0.03) 1339 31 (0.01) 21 (0.01) 9 (0.01) 5 (0.01) 2 (0.00) 1 (0.00) 1 (0.01) 1 (0.01) 1340 58 (0.02) 48 (0.02) 24 (0.02) 16 (0.02) 5 (0.01) 7 (0.03) -- 3 (0.04) n_20002_0_8 n_20002_0_9 n_20002_0_10 n_20002_0_11 n_20002_0_12 n_20002_0_13 n_20002_0_14 n_20002_0_15 Renal/urology 1192 1 (0.02) 2 (0.09) 2 (0.14) -- -- -- -- -- 1193 2 (0.05) 2 (0.09) -- -- 1 (0.20) -- -- 1 (0.78) 1194 5 (0.12) 4 (0.17) 4 (0.29) 2 (0.24) 2 (0.39) -- -- -- Hematology/dermatology 1451 1 (0.02) 2 (0.09) -- 3 (0.36) 1 (0.20) 1 (0.32) -- 1 (0.78) 1339 1 (0.02) -- -- -- -- -- -- -- 1340 1 (0.02) 1 (0.04) -- -- -- 1 (0.32) -- -- * 1192 - renal/kidney failure; 1193 - renal failure requiring dialysis ; 1194 - renal failure not requiring dialysis; 1451 - hereditary/genetic haematological disorder; 1339 - sickle cell disease; 1340 - thalassaemia

32. Inclusion criteria for GWAS of Hb concentration in UKB (502,536) (1) UK White only and born in UK (472,573) (2) 37-73 years old  40-70 years old (472,562) Exclusion criteria (3) Pregnant (459,095) (4) Self-reported cancer/s (420,119) (5) Self-reported renal/kidney failures (419,461) - Requiring or not requiring dialysis (6) Hereditary/genetic hematological disorder (419,013) - Sickle cell disease or thalassemia (7) Clotting disorder/excessive bleeding ( 418,226) - Low platelets/platelet disorder - Haemophilia - Essential thrombocytosis (1) Selection of variables to be used in UKB analyses

33. Clotting disorder/excessive bleeding Low platelets/platelet disorder - thrombocytopenia or a condition with low blood platelet count - platelets are colorless blood cells that help blood clot by clumping and forming plugs in blood vessel injuries - occurs as a result of a separate disorder, such as leukemia or an immune system problem, or can be a side effect of taking certain medications Haemophilia - a rare disorder in which blood doesn't clot normally because it lacks sufficient blood-clotting proteins (clotting factors ) - causes bleeding for a longer time after an injury than when blood clotted normally - *also a genetic disorder Essential thrombocytosis - an uncommon disorder in which your body produces too many blood platelets - causes fatigue and lightheadedness, headaches and vision changes, and increases risk of blood clots Reference: Mayo Foundation for Medical Education and Research (MFMER ) / Mayo Clinic

34. Haemachromatosis - a disease in which too much iron builds up in the body (iron overload), especially in the liver, heart, and pancreas - too much iron in the liver can cause an enlarged liver, liver failure, liver cancer, or cirrhosis (i.e., scarring of the liver) - too much iron in the heart can cause arrhythmias and heart failure - too much iron in the pancreas can lead to diabetes - primary hemochromatosis is caused by a defect in the genes that control how much iron to absorb from food - secondary hemochromatosis usually is the result of another disease or condition that causes iron overload Reference : US National Institutes of Health – National Heart, Lung, and Blood Institute

35. n_20002_0_0 n_20002_0_1 n_20002_0_2 n_20002_0_3 n_20002_0_4 n_20002_0_5 n_20002_0_6 n_20002_0_7 Hematology/dermatology 1445 121 (0.03) 117 (0.05) 84 (0.06) 52 (0.07) 36 (0.08) 18 (0.08) 13 (0.01) 6 (0.08) 1327 146 (0.04) 109 (0.05) 69 (0.05) 45 (0.06) 16 (0.04) 12 (0.05) 10 (0.08) 2 (0.03) 1328 26 (0.01) 15 (0.01) 13 (0.01) 5 (0.01) 2 (0.00) 4 (0.02) 1 (0.01) -- 1546 14 (0.00) 21 (0.01) 7 (0.00) 2 (0.00) 3 (0.01) 1 (0.00) 2 (0.02) -- Liver/biliary/pancreas problem 1507 27 (0.01) 24 (0.01) 20 (0.01) 4 (0.01) 7 (0.02) 3 (0.01) -- 1 (0.01) n_20002_0_8 n_20002_0_9 n_20002_0_10 n_20002_0_11 n_20002_0_12 n_20002_0_13 n_20002_0_14 n_20002_0_15 Hematology/dermatology 1445 2 (0.05) 1 (0.04) 4 (0.29) 1 (0.12) -- -- -- 1 (0.78) 1327 1 (0.02) 1 (0.04) -- 1 (0.12) 1 (0.20) -- -- 1 (0.78) 1328 -- 1 (0.04) -- -- -- -- -- -- 1546 -- -- -- -- -- -- -- -- Liver/biliary/pancreas problem 1507 -- -- -- -- -- -- -- -- Non-cancer illness/ es , self-reported * 1445 – clotting disorder/excessive bleeding; 1327 - low platelets/platelet disorder; 1328 – haemophilia ; 1546 - essential thrombocytosis 1507 - haemochromatosis

36. Inclusion criteria for GWAS of Hb concentration in UKB (502,536) (1) UK White only and born in UK (472,573) (2) 37-73 years old  40-70 years old (472,562) Exclusion criteria (3) Pregnant (459,095) (4) Self-reported cancer/s (420,119) (5) Self-reported renal/kidney failures (419,461) - Requiring or not requiring dialysis (6) Hereditary/genetic hematological disorder (419,013) - Sickle cell disease or thalassemia (7) Clotting disorder/excessive bleeding (418,226) - Low platelets/platelet disorder - Haemophilia - Essential thrombocytosis (8) HIV/AIDS (417,919) (9) Tuberculosis (415,949) ( 10) Tropical & travel-related infections including malaria and schistosomiasis /bilharzia (415,742) (1) Selection of variables to be used in UKB analyses

37. Reference: World Health Organization, 2017. Nutritional Anaemias : Tools for Effective Prevention and Control HIV/AIDS, Tuberculosis , and Tropical & Travel-Related Infections HIV/AIDS - anemia as one of the most common hematological abnormalities among afflicted persons, typically characterized as a normochromic and normocytic anaemia, with a low reticulocyte count, normal iron stores and an impaired erythropoietin response - indirect effects: opportunistic infections ( e.g. malaria, hookworm); nutritional deficiencies; and antiretroviral therapy having a negative effect on erythropoiesis - direct effects: affecting haematopoietic progenitor cells and decreasing responsiveness to erythropoietin - HIV infection is linked to pro-inflammatory cytokines and altered iron metabolism, leading to “anaemia of chronic disease/inflammation” Tuberculosis - anaemia is common among patients with TB and may be more common among those who are coinfected with TB and HIV - resulting from increased blood loss from haemoptysis (blood in sputum); decreased production of RBCs; poor appetite and food intake , leading to poor nutrient status; and anaemia of chronic disease/inflammation

38. Reference: World Health Organization, 2017. Nutritional Anaemias : Tools for Effective Prevention and Control HIV/AIDS, Tuberculosis , and Tropical & Travel-Related Infections Schistosomiasis - parasitic infection that can also lead to anaemia - similarly leads to blood loss, but may also contribute to anaemia through splenic sequestration of erythrocytes, increased haemolysis or anaemia of chronic disease Malaria - one of the primary causes of anaemia globally - Malaria disturbs iron metabolism in multiple ways and the mechanism for malaria-related anaemia is probably related to both increased haemolysis (erythrocyte destruction) and decreased production of red blood cells - hepcidin is upregulated in malaria infection, which probably contributes to anaemia through redistribution of iron to macrophages, and decreasing or preventing iron uptake from the diet

39. n_20002_0_0 n_20002_0_1 n_20002_0_2 n_20002_0_3 n_20002_0_4 n_20002_0_5 n_20002_0_6 n_20002_0_7 Viral infection 1439 228 (0.06) 134 (0.06) 68 (0.05) 16 (0.02) 13 (0.03) 5 (0.02) 4 (0.03) 1 (0.01) Bacterial infection 1440 869 (0.23) 689 (0.29) 468 (0.33) 233 (0.29) 146 (0.34) 69 (0.29) 42 (0.32) 16 (0.22) Tropical infections 1441 260 (0.07) 187 (0.08) 108 (0.08) 50 (0.06) 24 (0.06) 11 (0.05) 10 (0.08) 2 (0.03) 1443 8 (0.00) 14 (0.01) 10 (0.01) 4 (0.01) 1 (0.00) 4 (0.02) 1 (0.01) -- n_20002_0_8 n_20002_0_9 n_20002_0_10 n_20002_0_11 n_20002_0_12 n_20002_0_13 n_20002_0_14 n_20002_0_15 Viral infection 1439 2 (0.05) -- -- 1 (0.12) -- -- -- -- Bacterial infection 1440 9 (0.22) 5 (0.21) 3 (0.21) -- 2 (0.39) -- -- -- Tropical infections 1441 3 (0.07) 1 (0.04) -- 1 (0.12) 1 (0.20) -- -- -- 1443 -- -- -- -- -- -- -- -- Non-cancer illness/ es , self-reported * 1439 - hiv /aids; 1440 - tuberculosis ( tb ); 1441 - malaria; 1443 - schistosomiasis /bilharzia

40. Characterization of Hb by Fasting Time (N=415,742) Fast ing Time ( hr ) All (415,660) Hb (g/ dL ) 409 (0.10) 13.91 ± 1.2 (8.00-17.17) 1 19,457 (4.68) 14.13 ± 1.2 (0.20-20.14) 2 88,734 (21.34) 14.19 ± 1.2 (0.15-20.30) 3 122,353 (29.43) 14.20 ± 1.2 (0.12-22.27) 4 90,452 (21.76) 14.21 ± 1.2 (2.40-20.52) 5 49,349 (11.87) 14.22 ± 1.2 (0.31-19.48) 6 22,525 (5.42) 14.25 ± 1.2 (0.14-19.29) 7 6,101 (1.47) 14.28 ± 1.2 (0.97-18.42) 8 2,140 (0.51) 14.41 ± 1.3 (0.11-18.08) 9 740 (0.18) 14.53 ± 1.2 (10.50-17.92) 10 700 (0.17) 14.49 ± 1.3 (7.00-17.98) 11 629 (0.15) 14.54 ± 1.4 (9.10-18.16) 12 3,397 (0.82) 14.59 ± 1.3 (8.25-19.40) 13 1,371 (0.33) 14.53 ± 1.3 (6.69-18.90) 14 2,003 (0.48) 14.55 ± 1.3 (9.25-19.00) 15 1,769 (0.43) 14.46 ± 1.3 (9.78-18.90) 16 1,194 (0.29) 14.46 ± 1.3 (9.20-18.40) 17 790 (0.19) 14.56 ± 1.3 (8.80-19.40) 18 743 (0.18) 14.48 ± 1.3 (8.70-18.60) 19 258 (0.06) 14.64 ± 1.4 (9.70-18.80) 20 253 (0.06) 14.49 ± 1.3 (10.71-18.00) 21 101 (0.02) 14.41 ± 1.4 (11.90-17.48) 22 82 (0.02) 14.37 ± 1.5 (10.00-19.80) 23 50 (0.01) 14.55 ± 1.2 (11.41-16.67) 24 102 (0.02) 14.49 ± 1.2 (9.92-17.40) 25-28 16 (0.00) 29-32 4 (0.00) 33-36 3 (0.00) 37-40 1 (0.00) 41-44 -- 45-48 3 (0.00) *Missing 13 13.85 ± 1.3 (11.88-15.99)

41. Characterization of Hct by Fasting Time (N=415,742) Fast ing Time ( hr ) All (415,660) Hct (%) 409 (0.10) 13.91 ± 1.2 (8.00-17.17) 1 19,457 (4.68) 14.13 ± 1.2 (0.20-20.14) 2 88,734 (21.34) 14.19 ± 1.2 (0.15-20.30) 3 122,353 (29.43) 14.20 ± 1.2 (0.12-22.27) 4 90,452 (21.76) 14.21 ± 1.2 (2.40-20.52) 5 49,349 (11.87) 14.22 ± 1.2 (0.31-19.48) 6 22,525 (5.42) 14.25 ± 1.2 (0.14-19.29) 7 6,101 (1.47) 14.28 ± 1.2 (0.97-18.42) 8 2,140 (0.51) 14.41 ± 1.3 (0.11-18.08) 9 740 (0.18) 14.53 ± 1.2 (10.50-17.92) 10 700 (0.17) 14.49 ± 1.3 (7.00-17.98) 11 629 (0.15) 14.54 ± 1.4 (9.10-18.16) 12 3,397 (0.82) 14.59 ± 1.3 (8.25-19.40) 13 1,371 (0.33) 14.53 ± 1.3 (6.69-18.90) 14 2,003 (0.48) 14.55 ± 1.3 (9.25-19.00) 15 1,769 (0.43) 14.46 ± 1.3 (9.78-18.90) 16 1,194 (0.29) 14.46 ± 1.3 (9.20-18.40) 17 790 (0.19) 14.56 ± 1.3 (8.80-19.40) 18 743 (0.18) 14.48 ± 1.3 (8.70-18.60) 19 258 (0.06) 14.64 ± 1.4 (9.70-18.80) 20 253 (0.06) 14.49 ± 1.3 (10.71-18.00) 21 101 (0.02) 14.41 ± 1.4 (11.90-17.48) 22 82 (0.02) 14.37 ± 1.5 (10.00-19.80) 23 50 (0.01) 14.55 ± 1.2 (11.41-16.67) 24 102 (0.02) 14.49 ± 1.2 (9.92-17.40) 25-28 16 (0.00) 29-32 4 (0.00) 33-36 3 (0.00) 37-40 1 (0.00) 41-44 -- 45-48 3 (0.00) *Missing 13 13.85 ± 1.3 (11.88-15.99)

42. Characterization of Hb by Fasting Time (N=415,742) *4-hr fast groups Fast ing Time ( hr ) Frequency (%) Hb (g/ dL ) 0-4 321,405 (77.31) 14.20 ± 1.2 (0.12-22.27) 5-8 80,115 (19.27) 14.24 ± 1.2 (0.11-19.48) 9-12 5,466 (1.32) 14.56 ± 1.3 (7.00-19.40) 13-16 6,337 (1.52) 14.50 ± 1.3 (6.69-19.00) 17-20 2,044 (0.49) 14.53 ± 1.3 (8.70-19.40) 21-24 335 (0.08) 14.45 ± 1.3 (9.92-19.80) 25-28 16 (0.00) 14.34 ± 0.9 (13.00-16.01) 29-32 4 (0.00) 13.79 ± 0.9 (12.82-15.05) 33-36 3 (0.00) 14.62 ± 2.0 (12.52-16.40) 37-40 1 (0.00) 16.90 41-44 -- -- 45-48 3 (0.00) 14.89 ± 1.0 (13.80-15.80)

43. Characterization of Hct by Fasting Time (N=415,742) *4-hr fast groups Fast ing Time ( hr ) Frequency (%) Hct (%) 0-4 321,405 (77.31) 14.20 ± 1.2 (0.12-22.27) 5-8 80,115 (19.27) 14.24 ± 1.2 (0.11-19.48) 9-12 5,466 (1.32) 14.56 ± 1.3 (7.00-19.40) 13-16 6,337 (1.52) 14.50 ± 1.3 (6.69-19.00) 17-20 2,044 (0.49) 14.53 ± 1.3 (8.70-19.40) 21-24 335 (0.08) 14.45 ± 1.3 (9.92-19.80) 25-28 16 (0.00) 14.34 ± 0.9 (13.00-16.01) 29-32 4 (0.00) 13.79 ± 0.9 (12.82-15.05) 33-36 3 (0.00) 14.62 ± 2.0 (12.52-16.40) 37-40 1 (0.00) 16.90 41-44 -- -- 45-48 3 (0.00) 14.89 ± 1.0 (13.80-15.80)

44. Detection of Outliers in Hb Concentration (N=415,742) *Scatterplots of Hb vs Hct per 4-hr fast groups

45. Detection of Outliers in Hb Concentration (N=415,742) *Scatterplots of Hb vs Hct for 0 to 4 hr fasting

46. Detection of Outliers in Hb Concentration (N=415,742) *Scatterplots of Hb vs Hct for 0 to 4 hr fasting

47. Exclude participants with fasting time of 0 to 2 hr only and those who were fasted more than 12 hours

48. Final Characterization of Hb among Whites of UKB ( N=403,063) Al l (403,063) Male (188,468) Female (214,595) Hb, g/ dL 14.22 ± 1.2 ( 0.11 -22.27) 15.02  1.0 ( 0.12 -20.52) 13.51  0.9 ( 0.11 -22.27) *No missing values

49. Final Characterization of Hct among Whites of UKB (N=403,063) Al l (403,062) a Male (188,468) Female (214,595) b Hct , % 41.17 ± 3.5 (0.05-72.48) 43.34  3.0 (0.05-71.09) 39.26  2.8 (0.05-72.48) *Missing: a 1; b 1

50. Characterization of Hb by Age Categories (472,573 vs. 403,063) *5-yr age groups

51. Characterization of Hb by Age Categories (472,573 vs. 403,063) *5-yr age groups

52. Detection of Outliers in Hb Concentration (472,573 vs. 403,063) *Scatterplot of Hb vs Hct

53. Selection of UKB Participants Based on Proposed Inclusion-Exclusion Criteria 502,536 UKB participants (229,134 males and 273,402 females) 29,963 subjects who were non-White and not born in UK removed 11 subjects who were <40 and >70 years of age during assessment removed 13,467 subjects who were not genetically males, not genetically females, or pregnant removed 38,976 subjects who self-reported cancer removed 658 subjects who self-reported kidney failure removed 448 subjects who self-reported genetic hematological disorder removed n=472,573 n=472,562 n=459,095 n=420,119 n=419,461

54. Selection of UKB Participants Based on Proposed Inclusion-Exclusion Criteria 448 subjects who self-reported genetic hematological disorder removed 787 subjects who self-reported clotting disorder/excessive bleeding removed 307 subjects who self-reported HIV/AIDS removed 1,969 subjects who self-reported tuberculosis removed 658 subjects who self-reported tropical & travel-related infections removed 436 subjects with 0 hr fasting or had fasted for >24 hr removed n=418,226 n=417,919 n=415,949 n=415,742 n=419,013

55. Selection of UKB Participants Based on Proposed Inclusion-Exclusion Criteria 436 subjects with 0 hr fasting or had fasted for >24 hr removed 12,242 subjects without measured Hb level removed 403,063 UKB participants (188,468 males and 214,595 females) with 805,426 SNPS QC runs for genomic data n=415,306

56. Suggestions from March 02 Meeting with Dr. Kan and Dr. Huang 1 st OPTION: (1) Treat Hb as continuous outcome in GWAS (2) Categorize Hb-GRS in MR (i.e., tertiles or quartiles) 2 nd OPTION: (1) Categorize Hb levels in GWAS (also using tertiles?) All throughout analyses, PERFORM SEX STRATIFICATION (1) Generation of Hb-GRS by gender (2) Sex-stratified MR analyses

57. QC of UKB Genetic Data 126,541 subjects with identified genetic kinship removed 30 subjects who had withdrawn removed n=276,522 403,063 UKB participants (188,468 males and 214,595 females) with 805,426 SNPS 264 subjects with identified sex aneuploidy removed subjects with identified high heterozygosity or missing rate removed n=276,258 n=276,258 QC runs of genomic data using PLINK 4,050 subjects excluded in computing genetic PCs removed n=272,208

58. QC of UKB Genetic Data

59. QC of UKB Genetic Data

60. QC of UKB Genetic Data

61. Updates/Progress on Research Work Vanessa Joy Timoteo TIGP-MM Student March 19 2020

62. QC of UKB Genetic Data 126,471 subjects with identified genetic kinship removed *30 subjects who had withdrawn and 89 subjects with ambiguous sex removed n=276,344 402,815 UKB participants ( 188,314 males and 214,501 females) with 805,426 SNPS 4,054 subjects excluded in computing genetic PCs removed 258 subjects with identified sex aneuploidy removed n=272,290 n=272,032 QC runs of genomic data using PLINK 0 subjects with identified high heterozygosity or missing rate removed n=272,032 n=272,021

63. QC of UKB Genetic Data

64. QC of UKB Genetic Data

65. QC of UKB Genetic Data

66. QC of UKB Genetic Data using PLINK 71,119 variants removed due to high missingness rate per SNP (>5%); 293 subjects removed due to high missing genotype data (>2%) 272,021 UKB participants (128,782 males and 143,239 females) with 805,426 SNPS 734,307 variants in 271,728 subjects 137 subjects removed due to sex discrepancy 734,307 variants in 271,591 subjects 369,460 variants removed due to low MAF (<5%) 108,215 variants removed due to low MAF (<1%) 364,847 variants in 271,591 subjects 626,092 variants in 271,591 subjects 12,509 variants not in HWE removed (<10 -6 ) 44,224 variants not in HWE removed (<10 -6 ) 352,338 variants in 271,591 subjects 581,868 variants in 271,591 subjects 271,591 subjects (128,644 males and 142,947 females) with 341,743 autosomal SNPs 271,591 subjects (128,644 males and 142,947 females) with 565,783 autosomal SNPs

67. Proposed models for GWAS of Hb Concentration in UKB Crude Model 1 adjusted for sex, age groups, and genetic principal components -5-yr age groupings: 40-44, 45-49, 50-54, 55-59, 60-64, 65-70 -genetic principal components 1-20 * Sex-stratification analyses * Corrections for multiple testing using Bonferroni correction and false discovery rate of 5% (Bonferroni-corrected p-value < 0.05 and FDR < 0.05)

68. Autosomal SNPs with MAF >5% and HWE < 10 -6 (n=341,743 variants) Males (128,644) CHR Frequency Percent Cumulative Frequency 1 345 5.50 345 2 257 4.10 602 3 236 3.76 838 4 128 2.04 966 5 116 1.85 1082 6 3,030 48.32 4112 7 148 2.36 4260 8 130 2.07 4390 9 151 2.41 4541 10 123 1.96 4664 11 163 2.60 4827 12 248 3.95 5075 13 48 0.77 5123 14 80 1.28 5203 15 162 2.58 5365 16 169 2.69 5534 17 326 5.20 5860 18 45 0.72 5905 19 151 2.41 6056 20 48 0.77 6104 21 58 0.92 6162 22 109 1.74 6271 Comparison of Hb-associated SNPs in UKB from crude/unadjusted model Females (142,947) CHR Frequency Percent Cumulative Frequency 1 361 5.25 361 2 281 4.08 642 3 227 3.30 869 4 124 1.80 993 5 104 1.51 1097 6 3,183 46.27 4280 7 196 2.85 4476 8 151 2.20 4627 9 169 2.46 4796 10 168 2.44 4964 11 184 2.67 5148 12 287 4.17 5435 13 56 0.81 5491 14 89 1.29 5580 15 212 3.08 5792 16 185 2.69 5977 17 391 5.68 6368 18 58 0.84 6426 19 172 2.50 6598 20 70 1.02 6668 21 70 1.02 6738 22 141 2.05 6879 All (271,591) CHR Frequency Percent Cumulative Frequency 1 420 5.26 420 2 350 4.39 770 3 371 4.65 1141 4 157 1.97 1298 5 143 1.79 1441 6 3,298 41.34 4739 7 239 3.00 4978 8 148 1.86 5126 9 206 2.58 5332 10 236 2.96 5568 11 245 3.07 5813 12 297 3.72 6110 13 76 0.95 6186 14 122 1.53 6308 15 231 2.90 6539 16 269 3.37 6808 17 505 6.33 7313 18 80 1.00 7393 19 225 2.82 7618 20 86 1.08 7704 21 101 1.27 7805 22 173 2.17 7978

69. Autosomal SNPs with MAF >1% and HWE < 10 -6 (n=565,783 variants) Comparison of Hb-associated SNPs in UKB from crude/unadjusted model Males (128,644) CHR Frequency Percent Cumulative Frequency 1 298 4.88 298 2 235 3.85 533 3 207 3.39 740 4 116 1.90 856 5 107 1.75 963 6 3,087 50.60 4050 7 149 2.44 4199 8 111 1.82 4310 9 143 2.34 4453 10 129 2.11 4582 11 134 2.20 4716 12 255 4.18 4971 13 53 0.87 5024 14 75 1.23 5099 15 171 2.80 5270 16 165 2.70 5435 17 287 4.70 5722 18 38 0.62 5760 19 145 2.38 5905 20 41 0.67 5946 21 51 0.84 5997 22 104 1.70 6101 Females (142,947) CHR Frequency Percent Cumulative Frequency 1 330 4.80 330 2 255 3.71 585 3 222 3.23 807 4 125 1.82 932 5 109 1.58 1041 6 3,330 48.42 4371 7 184 2.68 4555 8 138 2.01 4693 9 165 2.40 4858 10 144 2.09 5002 11 166 2.41 5168 12 287 4.17 5455 13 55 0.80 5510 14 85 1.24 5595 15 228 3.32 5823 16 186 2.70 6009 17 386 5.61 6395 18 51 0.74 6446 19 158 2.30 6604 20 69 1.00 6673 21 72 1.05 6745 22 132 1.92 6877 All (271,591) CHR Frequency Percent Cumulative Frequency 1 396 4.85 396 2 366 4.48 762 3 363 4.45 1125 4 158 1.94 1283 5 137 1.68 1420 6 3,461 42.41 4881 7 234 2.87 5115 8 154 1.89 5269 9 199 2.44 5468 10 230 2.82 5698 11 245 3.00 5943 12 333 4.08 6276 13 75 0.92 6351 14 123 1.51 6474 15 258 3.16 6732 16 279 3.42 7011 17 508 6.22 7519 18 73 0.89 7592 19 214 2.62 7806 20 84 1.03 7890 21 100 1.23 7990 22 171 2.10 8161

70. Autosomal SNPs with MAF >5% and HWE < 10 -6 (n=341,743 variants) Males (128,644) CHR Frequency Percent Cumulative Frequency 1 -- -- -- 2 4 4.00 4 3 -- -- -- 4 -- -- -- 5 -- -- -- 6 57 57.00 61 7 2 2.00 63 8 -- -- -- 9 4 4.00 67 10 1 1.00 68 11 -- -- -- 12 9 9.00 77 13 -- -- -- 14 -- -- -- 15 -- -- -- 16 -- -- -- 17 13 13.00 90 18 -- -- -- 19 -- -- -- 20 -- -- -- 21 -- -- -- 22 10 10.00 100 Comparison of Top100 Hb-associated SNPs in UKB from crude/unadjusted model Females (142,947) CHR Frequency Percent Cumulative Frequency 1 -- -- -- 2 1 1.00 1 3 -- -- -- 4 -- -- -- 5 -- -- -- 6 71 71.00 72 7 3 3.00 75 8 -- -- -- 9 5 5.00 80 10 1 1.00 81 11 -- -- -- 12 9 9.00 90 13 -- -- -- 14 -- -- -- 15 -- -- -- 16 -- -- -- 17 -- -- -- 18 -- -- -- 19 -- -- -- 20 -- -- -- 21 -- -- -- 22 10 10.00 100 All (271,591) CHR Frequency Percent Cumulative Frequency 1 -- -- -- 2 3 3.00 3 3 -- -- -- 4 -- -- -- 5 -- -- -- 6 69 69.00 72 7 2 2.00 74 8 -- -- -- 9 5 5.00 79 10 1 1.00 80 11 -- -- -- 12 10 10.00 90 13 -- -- -- 14 -- -- -- 15 -- -- -- 16 -- -- -- 17 -- -- -- 18 -- -- -- 19 -- -- -- 20 -- -- -- 21 -- -- -- 22 10 10.00 100

71. Autosomal SNPs with MAF >1% and HWE < 10 -6 (n=565,783 variants) Males (128,644) CHR Frequency Percent Cumulative Frequency 1 -- -- -- 2 4 4.00 4 3 -- -- -- 4 -- -- -- 5 -- -- -- 6 57 57.00 61 7 2 2.00 63 8 -- -- -- 9 4 4.00 67 10 1 1.00 68 11 -- -- -- 12 9 9.00 77 13 -- -- -- 14 -- -- -- 15 -- -- -- 16 -- -- -- 17 13 13.00 90 18 -- -- -- 19 -- -- -- 20 -- -- -- 21 -- -- -- 22 10 10.00 100 Females (142,947) CHR Frequency Percent Cumulative Frequency 1 -- -- -- 2 1 1.00 1 3 -- -- -- 4 -- -- -- 5 -- -- -- 6 71 71.00 72 7 3 3.00 75 8 -- -- -- 9 5 5.00 80 10 1 1.00 81 11 -- -- -- 12 9 9.00 90 13 -- -- -- 14 -- -- -- 15 -- -- -- 16 -- -- -- 17 -- -- -- 18 -- -- -- 19 -- -- -- 20 -- -- -- 21 -- -- -- 22 10 10.00 100 All (271,591) CHR Frequency Percent Cumulative Frequency 1 -- -- -- 2 3 3.00 3 3 -- -- -- 4 -- -- -- 5 -- -- -- 6 69 69.00 72 7 2 2.00 74 8 -- -- -- 9 5 5.00 79 10 1 1.00 80 11 -- -- -- 12 10 10.00 90 13 -- -- -- 14 -- -- -- 15 -- -- -- 16 -- -- -- 17 -- -- -- 18 -- -- -- 19 -- -- -- 20 -- -- -- 21 -- -- -- 22 10 10.00 100 Comparison of Top100 Hb-associated SNPs in UKB from crude/unadjusted model

72. 33 Hb-decreasing variants in total sample, 24 among males, and 26 among females A number of Hb-increasing variants may explain why hemochromatosis is common in Europeans Males (128,644) CHR Frequency (-) Beta (+) Beta 1 -- -- -- 2 4 4 3 -- -- -- 4 -- -- -- 5 -- -- -- 6 57 10 47 7 2 2 8 -- -- -- 9 4 4 10 1 1 11 -- -- -- 12 9 9 13 -- -- -- 14 -- -- -- 15 -- -- -- 16 -- -- -- 17 13 13 18 -- -- -- 19 -- -- -- 20 -- -- -- 21 -- -- -- 22 10 4 6 Comparison of Top100 Hb-associated SNPs in UKB from crude/unadjusted model Females (142,947) CHR Frequency (-) Beta (+) Beta 1 -- -- -- 2 1 1 3 -- -- -- 4 -- -- -- 5 -- -- -- 6 71 13/12 58/59 7 3 3 8 -- -- -- 9 5 5 10 1 1 11 -- -- -- 12 9 9 13 -- -- -- 14 -- -- -- 15 -- -- -- 16 -- -- -- 17 -- -- -- 18 -- -- -- 19 -- -- -- 20 -- -- -- 21 -- -- -- 22 10 4 6 All (271,591) CHR Frequency (-) Beta (+) Beta 1 -- -- -- 2 3 3 3 -- -- -- 4 -- -- -- 5 -- -- -- 6 69 18 51 7 2 2 8 -- -- -- 9 5 5 10 1 1 11 -- -- -- 12 10 1 9 13 -- -- -- 14 -- -- -- 15 -- -- -- 16 -- -- -- 17 -- -- -- 18 -- -- -- 19 -- -- -- 20 -- -- -- 21 -- -- -- 22 10 4 6

73. Figure 1. Manhattan plot of 7,978 genome-wide Hb-associated SNPs in 271,591 UKB Whites after controlling FDR at 5%. * Red horizontal line shows the genome-wide significance threshold (p<5x10 -8 ).

74. Figure 2. Manhattan plot of 6,271 genome-wide Hb-associated SNPs in Males of UKB Whites after controlling FDR at 5%. * Red horizontal line shows the genome-wide significance threshold (p<5x10 -8 ).

75. Figure 3. Manhattan plot of 6,879 genome-wide Hb-associated SNPs in Females of UKB Whites after controlling FDR at 5%. * Red horizontal line shows the genome-wide significance threshold (p<5x10 -8 ).

76. Comparison of Hb-associated SNPs between UKB and TWB (Total Population) TMPRSS6 rs2413450 TMPRSS6 rs4820268 TMPRSS6 rs855791 FAM234A rs57794544 LUC7L rs58718637 SLC17A2 rs80215559 HK1 rs16926246 PRKCE rs10495928

77. Comparison of Hb-associated SNPs between UKB and TWB (Males) TMPRSS6 rs2413450 TMPRSS6 rs4820268 MPST rs228129 FAM234A rs57794544 LUC7L rs58718637 HK1 rs16926246 SLC17A2 rs80215559 PRKCE rs10495928

78. Comparison of Hb-associated SNPs between UKB and TWB (Females) FAM234A rs57794544 LUC7L rs58718637 SLC17A2 rs80215559 TMPRSS6 rs2413450 TMPRSS6 rs4820268 HK1 rs16926246 PRKCE rs10495928

79. Comparison of Top100 Hb-associated SNPs in UKB from crude/unadjusted model In total sample vs. males vs. females

80. Genes where Top 100 Hb-associated SNPs in UKB are found A number of genes not found in TWB and vice-versa Only PRKCE ( chr 2), ABO ( chr 9), and TMPRSS6 ( chr 22) are common in both ethnicities Chr Gene in UKB Gene in TWB 1 PCNX2 2 PRKCE PRKCE MGAT5 4 CFAP299 SLIT2 5 ADAMTS19 6 BTN1A1 CARMIL1 HFE HIST1H2B HIST1H2AC SLC17A1 SLC17A2 SLC17A3 TRIM38 ZKSCAN3 ZSCAN31 ATP6V1G2-DDX39B / DDX39B / MCCD1 7 PRKAG2 AGMO ASB4 9 ABO SURF4  ABO 10 HK1 Chr Gene in UKB Gene in TWB 12 ACAD10 ATXN2 CUX2 NAA25 PTPN11 SH2B3 TRAFD1 13 TPTE2 14 MBIP 16 FAM234A LUC7L RAB40C 17 OR4D1 18 CXCR4 22 TMPRSS6 TMPRSS6 MPST

81. Challenges/Problems encountered during UKB analyses: Model 1 adjusting for sex, 5-yr age groups, and genetic PCs 1-20 PLINK code : > plink -- bfile timoteo_ukb_MAF5autosomes --linear hide- covar -- covar UKB_covar_march16.txt keep- pheno -on-missing- cov -- covar -name SEX AGEGROUP_ASSESS_1 AGEGROUP_ASSESS_2 AGEGROUP_ASSESS_3 AGEGROUP_ASSESS_4 AGEGROUP_ASSESS_5 AGEGROUP_ASSESS_6 PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8 PC9 PC10 PC11 PC12 PC13 PC14 PC15 PC16 PC17 PC18 PC19 PC20 --adjust --out timoteo_ukb_MAF5autosomes_crude_model1 Start: March 17 (Tues), 12:30 AM End: March 18 (Wed), 7:00 PM  almost 2 day run Sex-stratified model 1 adjusting for 5-yr age groups and genetic PCs 1-20 resulted in errors  NEEDS TROUBLESHOOTING! PLINK message: Writing linear model association results to timoteo_ukb_MAF5autosomes_model1_males.assoc.linear ... done. Zero valid tests; --adjust skipped .  Consider sequential addition of covariates (try PCs 1-10 first)

82. Challenges/Problems encountered during UKB analyses:

83. Sequential Addition of Covariates Model adjusting for sex and 5-yr age groups resulted in 12,040 Hb-associated SNPs

84. Other concerns regarding future analyses: Do we further account/adjust for other covariates in the model? Model 2 further adjusting for BMI , alcohol consumption, and cigarette smoking (how about physical activity?) Model 3 further adjusting for monthly income (instead of educational attainment ) and assessment center How do we include age at menopause among females in our model? (0 for those not reaching menopause yet during assessment period ) Do we select all Hb-associated SNPs in our GWAS for GRS calculation? Targets: (1) Two-stage GWAS, (2) GWAS of hematocrit

85. Updates/Progress on Research Work Vanessa Joy Timoteo TIGP-MM Student February 27 2020

86. (1) Selection of variables to be used in UKB analyses Inclusion criteria for GWAS of Hb concentration in UKB (502,536) (1) UK White only (472,573) (2) 37-73 years old Exclusion criteria for GWAS of Hb concentration in UKB (2) Pregnant (372) (459,106) (3) Self-reported cancer/s (41,700) (420,130) (4) Self-reported renal/kidney failures, requiring or not requiring dialysis (419,472) (5) Hereditary/genetic hematological disorder (419,024) (6) Clotting disorder/excessive bleeding including low platelets/platelet disorder, haemophilia , essential thrombocytosis (418,237) (7) Haemachromatosis ( 418,167) (8) HIV/AIDS (417,860) (9) Tuberculosis (415,891) (10) Tropical & travel-related infections including malaria and schistosomiasis /bilharzia (415,684)

87. Age grouping used in analyses: Age groups used by the lab: 30-44, 45-64 , > 65 years old Proposed age groups: 30-44, 45-55 , > 56 years old -“The menopause is a natural part of ageing that usually occurs between 45 and 55 years of age, as a woman's oestrogen levels decline. In the UK, the average age for a woman to reach the menopause is 51 . ” – NHS, 2018 (online) -“ There are trade-offs in the selection of the appropriate age range for studies of menopausal symptoms. For cross-cultural work, we recommend the age range of 45–55 , but encourage culture-specific flexibility to sample women aged 40-60 to better embrace variability in reproductive aging where relevant.” – Melby et al, 2011. Overview of methods used in cross-cultural comparisons of menopausal symptoms and their determinants: Guidelines for Strengthening the Reporting of Menopause and Aging (STROMA) studies. Maturitas 70(2 ):99-109 .

88. Characterization of Hb Per 5-Yr Age-at-Menopause in Genetic Females (N=249,551) Age-at-Menopause groupings Females with Menopause (n=153,157) Hb, g/ dL <20 16 (0.01) 20-24 106 (0.07) 13.65 ± 1.1 (9.70-15.80) 25-29 469 (0.31) 13.59 ± 1.0 (10.39-16.70) 30-34 1,275 (0.83) 13.54 ± 1.0 (8.70-17.26) 35-39 3872 (2.53) 13.56 ± 1.0 (0.11-17.40) 40-44 12,966 (8.47) 13.57 ± 0.9 (6.01-22.27) 45-49 33,822 (22.08) 13.57 ± 0.9 (6.00-18.77) 50-54 68,907 (44.99) 13.60 ± 0.9 (0.15-20.08) 55-59 20,824 (13.60) 13.66 ± 0.9 (0.14-19.29) 60-64 937 (0.61) 13.64 ± 0.9 (9.90-17.10) >65 8 (0.01) 14.04 ± 1.0 (12.70-15.80) Prefer not to answer 281 (0.18) Do not know 9,637 (6.29)

89. QC of UKB Genetic Data using PLINK 69,609 variants removed due to high missingness rate per SNP (>5%); 290 subjects removed due to high missing genotype data (>2%) 272,021 UKB participants (128,782 males and 143,239 females) with 784,256 autosomal SNPS 714,647 variants in 271,731 subjects *check for sex discrepancy skipped 714,647 variants in 271,731 subjects 360,651 variants removed due to low MAF (<5%) 105,741 variants removed due to low MAF (<1%) 353,996 variants in 271,731 subjects 608,906 variants in 271,731 subjects 12,233 variants not in HWE removed (<10 -6 ) 43,088 variants not in HWE removed (<10 -6 ) 341,763 variants in 271,731 subjects 565,818 variants in 271,731 subjects 271,731 subjects (128,641 males and 143,090 females) with 341,763 autosomal SNPs 271,731 subjects (128,641 males and 143,090 females) with 565,818 autosomal SNPs