Clinical trial NCT04959318: Precision Nutrition Impact on Health-Related Behavior Change
Official title: Precision Nutrition Impact on Health-Related Behavior Change in Active Duty Service Members
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: NA
Conditions: Metabolic Syndrome
Keywords: nutrition
military
nutrigenomics
Lead sponsor: Madigan Army Medical Center
Sponsor class: FED
Collaborators: name: TriService Nursing Research Program
First posted: 2021-07-13
Enrollment: 138
Sex: ALL
Minimum age (years): 18
Maximum age (years): 45
Standard ages: ADULT
Accepts healthy volunteers: yes
Allocation: RANDOMIZED
Intervention model: PARALLEL
Intervention model description: Subjects were enrolled, submitted fasting blood sample, and returned for initial measurements when lab results were available. At this visit, randomization based on a random number generator and concealed allocation with sequentially numbered opaque envelopes took place. This allowed the first treatment/professional counseling session to be held the same day depending on group assignment.
Primary purpose: PREVENTION

Brief summary: A prospective, randomized, controlled trial enrolling up to 150 service members (SMs) from two sites; Joint Base Lewis McChord (JBLM) in the Northwest and Joint Base San Antonio (JBSA)-Lackland in the Southwest. A baseline genomic profile (70 genes/80 single nucleotide polymorphisms \[SNPs\]) augmented by common serum biomarkers specific to diet-related chronic disease (metabolic syndrome, cardiovascular disease \[CVD\], vitamin D deficiency) risk will be created. Subjects will be randomized to either personalized nutrition counseling or standard nutrition education for 6 weeks. This interval matches Service-run healthy weight initiatives such as the Army's current Fit for Performance Program. To promote self-care and engagement, a digital app will be utilized for 2 weeks for real-time health data capture with continuous feedback and will be validated with in-person RD interviews. Physical activity and injury data, sun exposure, and family history will help elucidate unique individual responses. Participant follow-up at 12 weeks will evaluate changes in anthropometrics and metabolic, cardiovascular, and vitamin D biomarkers.

Detailed description: Precision nutrition leverages the specificity of molecular and phenotypic differences in personalizing diet and lifestyle interventions. Specific Aims: 1) Examine the effectiveness of gene-based nutrition counseling on health-related behavior change in service members as measured by body weight, body mass index (BMI), blood glucose, lipids, 25-hydroxyvitamin (OH) D, %body fat (BF), waist circumference, and blood pressure; 2) Evaluate the feasibility of a digital application to accurately capture diet, activity, and sleep behaviors; and 3) Describe military-unique characteristics in demographics, diet, and lifestyle for northwest Army and southwest Air Force cohorts.

A baseline genomic profile will be created from 70 diet-responsive genes and 80 variants following amplicon sequencing on an Illumina MiSeq platform and will be informed by serum biomarkers specific to diet-related chronic disease risk (i.e. metabolic syndrome, vitamin D deficiency) for each subject. Risk variants were selected if minor allele frequency \> 5% and at least two published papers verified the link to the phenotype of interest. Treatment group receives gene-based nutrition counseling for six weekly sessions; Controls receive evidence-based nutrition pamphlets, all content directed at preventing metabolic syndrome. A digital app provides real-time health data capture with continuous feedback and is verified by in-person dietitian interviews. Both groups will also use study resources independently for six weeks, returning for final body composition and serum biomarkers after the twelve-week intervention. The control group receives the genomic profile with dietary recommendations upon study completion. Data analysis will examine between-group and by-cohort differences on primary anthropometric and biomarker outcomes.

Eligibility criteria: Inclusion Criteria:

* Active duty Army or Air Force
* Age 18-45
* Able to read and comprehend English
* Assigned to JBLM or JBSA-Lackland,
* Remaining on station for 5 months
* Consider self generally healthy
* History of or currently out of compliance with military fitness standards
* Willing to submit 2 blood samples including one for gene testing
* Willing to undergo 1 DEXA scan (JBLM only)
* Willing to participate in 6 weekly nutrition counseling sessions if assigned to treatment group

Exclusion Criteria:

* Currently diagnosed with an eating disorder
* Pregnant
* Current physical training profile (ie limitation)
* Pending deployment in next 5 months
* Pending retirement in next 5 months
* Pending permanent change of duty station in the next 5 months
* Currently has a pacemaker (contraindicated for bioelectrical impedance analysis)

Primary outcomes:
measure: Weight loss
timeFrame: 12-14 weeks
Secondary outcomes:
measure: Body fat
timeFrame: 12-14 weeks
measure: Waist circumference
timeFrame: 12-14 weeks
measure: Serum Cholesterol
timeFrame: 12-14 weeks
measure: Systolic blood pressure
timeFrame: 12-14 weeks
measure: Diastolic blood pressure
timeFrame: 12-14 weeks
measure: Serum glucose
timeFrame: 12-14 weeks
measure: Serum triglyceride
timeFrame: 12 -14 weeks
Other outcomes:
Locations:
city: Tacoma
country: United States
facility: Madigan Army Medical Center
state: Washington
Study officials:
affiliation: Madigan AMC
name: Mary S McCarthy, PhD
role: PRINCIPAL_INVESTIGATOR
References:
citation: Bray MS, Loos RJ, McCaffery JM, Ling C, Franks PW, Weinstock GM, Snyder MP, Vassy JL, Agurs-Collins T; Conference Working Group. NIH working group report-using genomic information to guide weight management: From universal to precision treatment. Obesity (Silver Spring). 2016 Jan;24(1):14-22. doi: 10.1002/oby.21381.
citation: de Toro-Martin J, Arsenault BJ, Despres JP, Vohl MC. Precision Nutrition: A Review of Personalized Nutritional Approaches for the Prevention and Management of Metabolic Syndrome. Nutrients. 2017 Aug 22;9(8):913. doi: 10.3390/nu9080913.
citation: Liang Y, Kelemen A. Shared polymorphisms and modifiable behavior factors for myocardial infarction and high cholesterol in a retrospective population study. Medicine (Baltimore). 2017 Sep;96(37):e7683. doi: 10.1097/MD.0000000000007683.
citation: Povel CM, Boer JM, Onland-Moret NC, Dolle ME, Feskens EJ, van der Schouw YT. Single nucleotide polymorphisms (SNPs) involved in insulin resistance, weight regulation, lipid metabolism and inflammation in relation to metabolic syndrome: an epidemiological study. Cardiovasc Diabetol. 2012 Oct 29;11:133. doi: 10.1186/1475-2840-11-133.
citation: Corella D, Coltell O, Mattingley G, Sorli JV, Ordovas JM. Utilizing nutritional genomics to tailor diets for the prevention of cardiovascular disease: a guide for upcoming studies and implementations. Expert Rev Mol Diagn. 2017 May;17(5):495-513. doi: 10.1080/14737159.2017.1311208. Epub 2017 Apr 3.
citation: Joseph MS, Konerman MA, Zhang M, Wei B, Brinza E, Walden P, Jackson EA, Rubenfire M. Long-term outcomes following completion of a structured nutrition and exercise lifestyle intervention program for patients with metabolic syndrome. Diabetes Metab Syndr Obes. 2018 Nov 15;11:753-759. doi: 10.2147/DMSO.S175858. eCollection 2018.
citation: Celis-Morales C, Livingstone KM, Marsaux CF, Forster H, O'Donovan CB, Woolhead C, Macready AL, Fallaize R, Navas-Carretero S, San-Cristobal R, Kolossa S, Hartwig K, Tsirigoti L, Lambrinou CP, Moschonis G, Godlewska M, Surwillo A, Grimaldi K, Bouwman J, Daly EJ, Akujobi V, O'Riordan R, Hoonhout J, Claassen A, Hoeller U, Gundersen TE, Kaland SE, Matthews JN, Manios Y, Traczyk I, Drevon CA, Gibney ER, Brennan L, Walsh MC, Lovegrove JA, Alfredo Martinez J, Saris WH, Daniel H, Gibney M, Mathers JC. Design and baseline characteristics of the Food4Me study: a web-based randomised controlled trial of personalised nutrition in seven European countries. Genes Nutr. 2015 Jan;10(1):450. doi: 10.1007/s12263-014-0450-2. Epub 2014 Dec 10.
citation: Locke AE, Kahali B, Berndt SI, Justice AE, Pers TH, Day FR, Powell C, Vedantam S, Buchkovich ML, Yang J, Croteau-Chonka DC, Esko T, Fall T, Ferreira T, Gustafsson S, Kutalik Z, Luan J, Magi R, Randall JC, Winkler TW, Wood AR, Workalemahu T, Faul JD, Smith JA, Zhao JH, Zhao W, Chen J, Fehrmann R, Hedman AK, Karjalainen J, Schmidt EM, Absher D, Amin N, Anderson D, Beekman M, Bolton JL, Bragg-Gresham JL, Buyske S, Demirkan A, Deng G, Ehret GB, Feenstra B, Feitosa MF, Fischer K, Goel A, Gong J, Jackson AU, Kanoni S, Kleber ME, Kristiansson K, Lim U, Lotay V, Mangino M, Leach IM, Medina-Gomez C, Medland SE, Nalls MA, Palmer CD, Pasko D, Pechlivanis S, Peters MJ, Prokopenko I, Shungin D, Stancakova A, Strawbridge RJ, Sung YJ, Tanaka T, Teumer A, Trompet S, van der Laan SW, van Setten J, Van Vliet-Ostaptchouk JV, Wang Z, Yengo L, Zhang W, Isaacs A, Albrecht E, Arnlov J, Arscott GM, Attwood AP, Bandinelli S, Barrett A, Bas IN, Bellis C, Bennett AJ, Berne C, Blagieva R, Bluher M, Bohringer S, Bonnycastle LL, Bottcher Y, Boyd HA, Bruinenberg M, Caspersen IH, Chen YI, Clarke R, Daw EW, de Craen AJM, Delgado G, Dimitriou M, Doney ASF, Eklund N, Estrada K, Eury E, Folkersen L, Fraser RM, Garcia ME, Geller F, Giedraitis V, Gigante B, Go AS, Golay A, Goodall AH, Gordon SD, Gorski M, Grabe HJ, Grallert H, Grammer TB, Grassler J, Gronberg H, Groves CJ, Gusto G, Haessler J, Hall P, Haller T, Hallmans G, Hartman CA, Hassinen M, Hayward C, Heard-Costa NL, Helmer Q, Hengstenberg C, Holmen O, Hottenga JJ, James AL, Jeff JM, Johansson A, Jolley J, Juliusdottir T, Kinnunen L, Koenig W, Koskenvuo M, Kratzer W, Laitinen J, Lamina C, Leander K, Lee NR, Lichtner P, Lind L, Lindstrom J, Lo KS, Lobbens S, Lorbeer R, Lu Y, Mach F, Magnusson PKE, Mahajan A, McArdle WL, McLachlan S, Menni C, Merger S, Mihailov E, Milani L, Moayyeri A, Monda KL, Morken MA, Mulas A, Muller G, Muller-Nurasyid M, Musk AW, Nagaraja R, Nothen MM, Nolte IM, Pilz S, Rayner NW, Renstrom F, Rettig R, Ried JS, Ripke S, Robertson NR, Rose LM, Sanna S, Scharnagl H, Scholtens S, Schumacher FR, Scott WR, Seufferlein T, Shi J, Smith AV, Smolonska J, Stanton AV, Steinthorsdottir V, Stirrups K, Stringham HM, Sundstrom J, Swertz MA, Swift AJ, Syvanen AC, Tan ST, Tayo BO, Thorand B, Thorleifsson G, Tyrer JP, Uh HW, Vandenput L, Verhulst FC, Vermeulen SH, Verweij N, Vonk JM, Waite LL, Warren HR, Waterworth D, Weedon MN, Wilkens LR, Willenborg C, Wilsgaard T, Wojczynski MK, Wong A, Wright AF, Zhang Q; LifeLines Cohort Study; Brennan EP, Choi M, Dastani Z, Drong AW, Eriksson P, Franco-Cereceda A, Gadin JR, Gharavi AG, Goddard ME, Handsaker RE, Huang J, Karpe F, Kathiresan S, Keildson S, Kiryluk K, Kubo M, Lee JY, Liang L, Lifton RP, Ma B, McCarroll SA, McKnight AJ, Min JL, Moffatt MF, Montgomery GW, Murabito JM, Nicholson G, Nyholt DR, Okada Y, Perry JRB, Dorajoo R, Reinmaa E, Salem RM, Sandholm N, Scott RA, Stolk L, Takahashi A, Tanaka T, van 't Hooft FM, Vinkhuyzen AAE, Westra HJ, Zheng W, Zondervan KT; ADIPOGen Consortium; AGEN-BMI Working Group; CARDIOGRAMplusC4D Consortium; CKDGen Consortium; GLGC; ICBP; MAGIC Investigators; MuTHER Consortium; MIGen Consortium; PAGE Consortium; ReproGen Consortium; GENIE Consortium; International Endogene Consortium; Heath AC, Arveiler D, Bakker SJL, Beilby J, Bergman RN, Blangero J, Bovet P, Campbell H, Caulfield MJ, Cesana G, Chakravarti A, Chasman DI, Chines PS, Collins FS, Crawford DC, Cupples LA, Cusi D, Danesh J, de Faire U, den Ruijter HM, Dominiczak AF, Erbel R, Erdmann J, Eriksson JG, Farrall M, Felix SB, Ferrannini E, Ferrieres J, Ford I, Forouhi NG, Forrester T, Franco OH, Gansevoort RT, Gejman PV, Gieger C, Gottesman O, Gudnason V, Gyllensten U, Hall AS, Harris TB, Hattersley AT, Hicks AA, Hindorff LA, Hingorani AD, Hofman A, Homuth G, Hovingh GK, Humphries SE, Hunt SC, Hypponen E, Illig T, Jacobs KB, Jarvelin MR, Jockel KH, Johansen B, Jousilahti P, Jukema JW, Jula AM, Kaprio J, Kastelein JJP, Keinanen-Kiukaanniemi SM, Kiemeney LA, Knekt P, Kooner JS, Kooperberg C, Kovacs P, Kraja AT, Kumari M, Kuusisto J, Lakka TA, Langenberg C, Marchand LL, Lehtimaki T, Lyssenko V, Mannisto S, Marette A, Matise TC, McKenzie CA, McKnight B, Moll FL, Morris AD, Morris AP, Murray JC, Nelis M, Ohlsson C, Oldehinkel AJ, Ong KK, Madden PAF, Pasterkamp G, Peden JF, Peters A, Postma DS, Pramstaller PP, Price JF, Qi L, Raitakari OT, Rankinen T, Rao DC, Rice TK, Ridker PM, Rioux JD, Ritchie MD, Rudan I, Salomaa V, Samani NJ, Saramies J, Sarzynski MA, Schunkert H, Schwarz PEH, Sever P, Shuldiner AR, Sinisalo J, Stolk RP, Strauch K, Tonjes A, Tregouet DA, Tremblay A, Tremoli E, Virtamo J, Vohl MC, Volker U, Waeber G, Willemsen G, Witteman JC, Zillikens MC, Adair LS, Amouyel P, Asselbergs FW, Assimes TL, Bochud M, Boehm BO, Boerwinkle E, Bornstein SR, Bottinger EP, Bouchard C, Cauchi S, Chambers JC, Chanock SJ, Cooper RS, de Bakker PIW, Dedoussis G, Ferrucci L, Franks PW, Froguel P, Groop LC, Haiman CA, Hamsten A, Hui J, Hunter DJ, Hveem K, Kaplan RC, Kivimaki M, Kuh D, Laakso M, Liu Y, Martin NG, Marz W, Melbye M, Metspalu A, Moebus S, Munroe PB, Njolstad I, Oostra BA, Palmer CNA, Pedersen NL, Perola M, Perusse L, Peters U, Power C, Quertermous T, Rauramaa R, Rivadeneira F, Saaristo TE, Saleheen D, Sattar N, Schadt EE, Schlessinger D, Slagboom PE, Snieder H, Spector TD, Thorsteinsdottir U, Stumvoll M, Tuomilehto J, Uitterlinden AG, Uusitupa M, van der Harst P, Walker M, Wallaschofski H, Wareham NJ, Watkins H, Weir DR, Wichmann HE, Wilson JF, Zanen P, Borecki IB, Deloukas P, Fox CS, Heid IM, O'Connell JR, Strachan DP, Stefansson K, van Duijn CM, Abecasis GR, Franke L, Frayling TM, McCarthy MI, Visscher PM, Scherag A, Willer CJ, Boehnke M, Mohlke KL, Lindgren CM, Beckmann JS, Barroso I, North KE, Ingelsson E, Hirschhorn JN, Loos RJF, Speliotes EK. Genetic studies of body mass index yield new insights for obesity biology. Nature. 2015 Feb 12;518(7538):197-206. doi: 10.1038/nature14177.