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The Utah Study of Fertility

Initiative to Study Exceptional Longevity. Advisory Panel on Exceptional Longevity (APEL) ... factors that contribute to exceptional longevity (EL) and reduce risks across major ...

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The Utah Study of Fertility

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  1. The Utah Study of Fertility, Longevity & Agingand the Utah Population DatabaseKen R. Smith(ken.smith@fcs.utah.edu) Supported by NIA grants AG00767, AG14495, and AG13478.

  2. How Long Will You Live?… in Good Health?Is there a way to know?Is there a way to change it?

  3. Longevity Game – Northwestern Mutual Gender Age Family History BMI Blood Pressure Stress Exercise Diet Seat Belt Driving Style Alcohol Smoking Illicit Drug Use http://www.nmfn.com/tn/learnctr--lifeevents--longevity_end

  4. Longevity Calculator - New England Centenarian Study Tobacco Diet Alcohol Air pollution Coffee/tea Aspirin Flossing History of CVD Tanning Social Support Stress Family Hx of Longevity Exercise Vitamins Gender Age

  5. Traditional Method • Life Tables • Gender • Age • Place • Year

  6. Years of Life Remaining:Utah Males 2001 Years Age

  7. Years of Life Remaining: Utah Females 2001 Years Age

  8. Difference in Remaining Years of Life: Female Advantage over Males 2001, Utah Years Age

  9. Years of Life Remaining:US and Utah Males 2001 Years Age

  10. Years of Life Remaining: US and Utah Females 2001 Years Age

  11. Objectives • Why study exceptional familial longevity? • NIA support • Utah Longevity Study • Measures • Importance of the Utah Population Database • Research Highlights • Final thoughts

  12. What is Possiblefor Achieving a Healthy Life Span?Look to the record-holders.

  13. LONGEST LIVED HUMAN WITH AUTHENTICATED RECORDS Jeanne Louise Calment, Paris Died 1997 at age 122 LONGEST LIVING HUMAN WITH AUTHENTICATED RECORDS 116-year-old Elizabeth “Lizzie” Bolden. Memphis, Tenn.

  14. What allowed these individuals to live so long? Aged slowly & thus avoided serious fatal diseases Science, 2-28-2003

  15. National Institute on AgingInitiative to Study Exceptional Longevity • Advisory Panel on Exceptional Longevity (APEL) • Find genetic & environmental factors that contribute to exceptional longevity (EL) and reduce risks across major age-related diseases • Find homogenous subgroups that comprise the long-lived population (e.g., familial patterns of longevity)

  16. Utah Study of Fertility, Longevity, and Aging (USFLAG) (National Institute on Aging) 2 Resistance to chronic diseases and environmental stressors Rank UPDB pedigrees in terms of family pattern of longevity past 65 Psycho-social, biological, genetic markers associated with exceptional survival among relatives around age 90+ 3 1 • Do offspring of long-lived parents age more slowly than controls 4

  17. Utah Study of Fertility, Longevity, and Aging (USFLAG) (National Institute on Aging)

  18. Demographic Factors Risk/Lifestyle Factors Medical History Reproductive History Cognitive Functioning Instrumental/Activities of Daily Living Depression Stress Resiliency Blood Measures Serum Cholesterol Glycosylated Hemoglobin C-reactive protein DHEA/DHEAS Albumin Uric Acid Creatinine WBC DNA Immortal cell lines Genome Wide Scan Telomere Length Mutations in mtDNA APOE Clinical Measures Grip Strength Blood and Pulse Pressure Heart Rate Lung Function Body Mass Index Body Temperature Morbidity (CMS Medicare claims) Mortality (cause of death) Selected Measures

  19. UPDB and FLAG

  20. Aging Research Advances ThroughNovel Linkages to UPDB Centers for Medicare & Medicaid Services 1991-2002 400,000 Utahns age 65+ Cache County Study on Memory, Health & Aging Ron Munger, JoAnn Tschanz, Maria Norton USU Kathleen Welsh-Bohmer Duke

  21. Research Highlights:A Sampler

  22. Does Exceptional Survival Run in Families?Does a Family History of Extreme Longevity Protect Against Major Age-Related Diseases?

  23. Recurrence Risks of Extreme Longevity (Lived Past 99th Percentile of Excess Longevity) in Various Classes of Relatives (UPDB) Extreme Longevity Runs in Families Parent, Sibling Gparent, Gchild, Aunt, Uncle, Niece, Nephews 1st Cousin Once Removed 1st Cousins Kerber, O’Brien, Smith and Cawthon, 2001, J of Gerontology

  24. Relative Risk of Mortality:Top 25% vs. Bottom 25% of Familial Longevity (UPDB) Extreme Familial Longevity Reduces Risk at Most Ages Worse Cancer Cerebrovascular Diabetes Better Heart Age O’Brien, Kerber, Smith, Mineau, submitted, 2006

  25. Are there factors that we can observe in midlife (age 50) in UPDB that predict lower mortality in later years?The case of late female fertility(or if you can measure it, late natural menopause)

  26. Relative Risk of Living to 100 Vs. Dying Before Age 85 Among Women By Age at Last Birth (Among Women Surviving to Age 60; Born <=1900) (UPDB) Late Fertile Women More Likely to be Centenarians Relative Risk Age at Last Birth Controls for Mormon/Non-Mormon status, birth year, parity, age at first birth Reference group: Women whose Age at Last Birth is 37 to 42 years of age Smith, Mineau, Bean, Social Biology, 2002

  27. Reduced Risk of Mortality from Leading Causes of Death Among Females (60+) with Very Late Fertility (>age 45) vs. Controls (UPDB) Late Fertile Women Less Prone to Major Causes of Death

  28. Relative Risk for Late vs. Average Age (<=41) at Last Birth Between Female Members 55 or Older of Lineages Selected for Exceptional Longevity & Control Lineages >=3 Probands per Lineage 8.9 Women from LL Pedigrees are More Prone to be Late Fertile Adjusts for birth date, age at first birth, LDS affiliation; Bars represent 95% CI; N=440; All subjects lived to age 55.

  29. Relative Risks for Mortality for Brothers Living to Age 50 byMaximum Age at Last Birth of Sisters Who Survived to Age 50(Reference Group: Sisters’ with Max Age at Last Birth below 50th Pct) Brothers of Late Fertile Women Live Longer Relative Risk UT = Utah Population Database (n=29,445 males)

  30. Telomeres and Longevity As cells divide, telomeres shorten with increasing age due to a decline in the enzyme telomerase Short telomeres trigger cell death & cellular senescence (possibly as a protection against cancer) and are associated with aging and death UGRP (Utah Genetic Reference Project) families linked to UPDB

  31. Those with longer telomeres in blood DNA live longer among the elderly, controlling for age Years Since Blood Draw Cawthon, Smith, O’Brien, Sivatchenko, Kerber, Lancet, 2003

  32. Women Men Years Since Blood Draw Cawthon, Smith, O’Brien, Sivatchenko, Kerber, Lancet, 2003

  33. Age 60-74 Age 75+ Cawthon, Smith, O’Brien, Sivatchenko, Kerber, Lancet, 2003

  34. How are the Middle-agedand Young Elderly of the Exceptional Survivors Doing?

  35. Relative Risk of Disease: Offspring of Proband vs. Controls Odds Ratio 69 offspring 1569 NHANES controls Controls for age, gender, education, marital status

  36. Cache County Study on Memory, Health & Aging Cache Co.

  37. Genetic Markers Associated with Aging and Survival that are Linked to the UPDB • ε4 allele: • Risk of cardiovascular disease • Alzheimer’s Disease • ε2 allele • More frequent in centenarians • Association between APOE genotype and cause-specific mortality • Modified by indicators of rates of aging • Possible because of record linkage to UPDB

  38. Mortality Rate Ratios for APOE Genotypes (ε33 is reference) All-Cause Cardiovascular (633) ε22 ε23ε24 ε34 ε44 ε22 ε23ε24 ε34 ε44 Respiratory (176) Cancer (249) ε22 ε23ε24 ε34 ε44 ε22 ε23ε24 ε34 ε44

  39. Mortality Rate Ratios for APOE Genotypes (ε33 is reference) Nervous (AD, Parkinson) (84) Endocrine (Diabetes) (62) ε22 ε23ε24 ε34 ε44 ε22 ε23ε24 ε34 ε44 Digestive System (57) Mental Disorders (42) ε22 ε23ε24 ε34 ε44 ε22 ε23ε24 ε34 ε44

  40. Effects of APOE Genotype on All-Cause Mortality by Familial Longevity Pedigrees of Average Longevity Long-Lived Pedigrees ε22 ε23ε24 ε34 ε44 ε22 ε23ε24 ε34 ε44 Interaction between FEL and ε34 & ε44, p<.05

  41. Medicare Claims • 65-69 year olds (n=28,000) • 1998-2002 • Medicare Claims in Utah • Compare top 10% for familial longevity to the rest • 11.2 fewer claims • 8 fewer claims for heart disease, stroke, cancer, and diabetes combined • 40% more likely to have made no claims for these four leading conditions

  42. Final Thoughts • Study not designed with personalized medicine in mind • Potential for identifying measures that capture rates of aging that predict risks from multiple diseases • Long-lived as a source of information about low disease risk • Value of deep family history of longevity to supplement family medical history • Value of UPDB

  43. Genetics and Genetic Epidemiology Richard Cawthon Richard Kerber Elizabeth O’Brien Demography Geri Mineau Ken Smith Biostatistics Ken Boucher Gilda Garibotti Psychology Cindy Berg Project Manager Diana Lane Reed Database Manager Alison Fraser Project Coordinators Heather Anderson Jahn Barlow Database Linkage/Programmers Richard Pimentel Heidi Hanson Study Coordinator Michelle Robinson Phlebotomists Kellie Littlefield Jayci Bash Layah Steinberg-Moss Informatics Dinny Berry Research Administration Camille Phillips CRC Sayed Ahmed USFLAG Team

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