Henry J. Thompson Cancer Prevention Laboratory Department of Horticulture and Landscape Architecture Colorado State University, Fort Collins, CO. ([email protected]) Crops For Health: A Vision for Agriculture as An Instrument of Public Health Can It Save Your Life?
Welcome message from author
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript
Henry J. Thompson Cancer Prevention Laboratory
Department of Horticulture and Landscape Architecture
Colorado State University, Fort Collins, CO. ([email protected])
Crops For Health: A Vision for Agriculture as An Instrument of Public Health
Can It Save Your Life?
Your Goal: How Does This Apply To Me?
My Goal:
Get You To Think New Thoughts About Food and Your Health
What does success look like?
You go home and try new things
Save A Million Lives:
We need Agriculture to become
Instrument of Public Health
to accomplish this goal
Biomedical Agriculture
Crops for Health
World Health Organization Report
Fruit and vegetables are important
components of a healthy diet, and their
sufficient daily consumption could help
prevent major diseases, such as cardiovascular
diseases and certain cancers. Overall, it is
estimated that up to 2.7 million lives could
potentially be saved each year if fruit and
vegetable consumption were sufficiently
increased.
Plant Food (VF)-Health Puzzle
Eat mostly
foods of plant
origin for
cancer
prevention
No convincing
epidemiological
evidence that any
specific type of
plant food (V,F,G)
or nutrient inhibits
cancer of any type
WCRF-AICR: Food, Nutrition,
Physical Activity and the Prevention of
Cancer: a Global Perspective. Nov.1-2,
2007
Possible Explanations
•Plant foods don’t have any effect on the development of
chronic diseases like cancer.
•The way humankind eats plant foods doesn’t have any
effect on the development of chronic diseases like cancer.
•The way scientists measure plant food consumption is
insufficient to detect true effects on health that exist.
Crops for Health
•Plant food consumption (VF) is insufficient.
•Human eating patterns lack sufficient botanical diversity to
promote health/prevent disease.
•Insufficient emphasis on Staple Food Crops vs VF
•Varieties (cultivars) within a food crop differ markedly in
protective activity.
Urinary 8-EPG
0.0
0.2
0.4
0.6
0.8
1.0
T1 T2 T3 T4 T5
ng
/mg
Creati
nin
e
A B
200
400
600
800
1000
1200
1400
1600
0 2 4 6 8
Week on Study
Uri
nary
8-I
so
pro
sta
ne F
-2α
, p
g/m
g c
reat.
Low VF 1
Low VF 2
Low VF 3
Low VF 4
High VF 1
High VF 2
High VF 3
High VF 4
Thompson et al: AJCN, 2005
Possible Explanations
•Plant foods don’t have any effect on the development of
chronic diseases like cancer.
•The way humankind eats plant foods doesn’t have any
effect on the development of chronic diseases like cancer.
•The way scientists measure plant food consumption is
insufficient to detect true effects on health that exist.
Crops for Health
•Plant food consumption (VF) is insufficient.
•Human eating patterns lack sufficient botanical diversity to
promote health/prevent disease.
•Insufficient emphasis on Staple Food Crops vs VF
•Varieties (cultivars) within a food crop differ markedly in
protective activity.
Ackee, Lychee, Longan, Maple Syrup
Cacao (Cocoa, Chocolate)
Mango, Cashews
Grapefruit, Kumquat, Lemon, Lime Orange, Tangerine
Papaya Arugula, Bok Choy, Broccoli, Brussels sprouts, Cabbage, Cauliflower, Collard greens, Daikon, Kale, Kohlrabi, Horseradish, Mustard greens, Radish, Rutabaga, Turnip, Turnip greens, Watercress
Asparagus
Barley, Corn, Lemongrass, Millet, Oat, Rye, Rice, Wheat, Sugarcane, Sorghum
Cardamom, Ginger
Banana, Plantain
Pineapple
Chives, Garlic, Leeks, Shallot, Onion
Date, Coconut, Palm oil
Mace, Nutmeg
Custard Apple, Pawpaw, Sugar Apple
Yam
Avocado, Cinnamon, Sassafras
Black Pepper
Grape
Black currant
Poppy
Tea
Coffee
Brazil nut
Blueberry, Cranberry, Lingonberry
Chinese Gooseberry, Kiwi
Beet, Beet greens, Orache, Spinach, Swiss chard, Quinoa
Prickly pear cactus
Rhubarb, Sorrel
Star anise
Carrot, Celery, Chervil, Coriander, Dill, Fennel, Parsley, Parsnip
Ginseng
Artichoke, Chamomile, Chicory, Dandelion, Endive, Lettuce, Radicchio, Sunflower, Tarragon
Olive
Basil, Lavender, Marjoram, Mint, Oregano, Rosemary, Sage, Thyme
Lemon verbena
Sesame
Sweet potato
Eggplant, Peppers (bell, chili, sweet, Pimento), Potato, Tomato
Black walnut, English walnut
Filbert, Hazelnut
Cucumber, Gourds, Melon, Pumpkin, Squash, Watermelon
Beans, Jicama, Lentils, Licorice, Peas, Peanuts, Soybean
Almond, Apple, Apricot, Blackberry, Cherry, Nectarine, Peach, Plum, Raspberry, Strawberry, Quince
Allspice
Cassava
Variety and moderation are necessary for achieving dietary diversity - the foundation of a nutritious, well-balanced diet that may promote health and prevent disease. However, an evidence-based consensus does not exist regarding food combinations that reduce chronic disease risk. In an effort to better deal with this impasse, we recommend the guidelines promoting plant food-rich diets provide more detail about achieving variety and moderation. A rationale is presented for using botanical families as a tool to systematically increase the phytochemical diversity of the diet. Acknowledging the rapidly changing cultural norms with respect to foods, including the impact of the global market place and advances in food science and technology, the method proposed here uses the botanical family concept to design patterns of food consumption that capitalize on the richness of potentially beneficial chemicals in widely available plant-based foods.
Plants that provide foods consumed by human beings arose at different times during evolution. This relational tree shows the relationships that exist among commonly eaten foods. Foods on the same branches of the tree share more similarities, genetically and chemically than foods that are further separated on the tree. The relationships shown are based on Linnean classification and were determined based on information available from the tree of life web project (http://tolweb.org/tree/). Only angiosperms are shown (does not include gymnosperms, seedless vascular and seedless non-vascular). Blair Dorsey, John N. McGinley and Henry J. Thompson Disclaimer: Information presented is considered a work in progress (updated 7-15-2009).
Sapindaceae
Malvaceae
Anacardiaceae
Rosaceae Moraceae
Fabaceae (Leguminosae)
Convulvulaceae
Solanaceae
Verbenaceae
Pedaliaceae
Lamiaceae (Labiatae)
Oleaceae
Asteraceae (Compositae)
Apiaceae (Umbelliferae)
Araliaceae
Actinidaceae
Ericaceae
Chenopodiaceae
Rubiaceae
Lecythidaceae
Theaceae
Grossulariaceae
Juglandaceae
Cucurbitaceae
Betulaceae
Breadfruit, Fig, Mulberry, Jackfruit
Myrtaceae
Vitaceae
Piperaceae
Lauraceae
Cactaceae
Polygonaceae
Papaveraceae
Illiciaceae
Annonaceae
Myristicaceae
Arecaceae
Dioscoreaceae
Muscaceae
Zingiberaceae
Euphorbiaceae
Bromeliaceae
Poaceae (Gramineae)
Asparagaceae (Liliaceae)
Alliaceae (Liliceae)
Rutaceae
Malvaceae Brassicaceae (Cruciferae)
Evolutionary Tree of Plant-based Foods
0.00 0.50 1.00 1.50 2.00 2.50
Actinidiaceae
Chenopodiaceae
Convolvulaceae
Cucurbitaceae
Graminae
Liliaceae
Rosaceae
Solanaceae
Vitaceae
n-a-day
17 family
5 family
DAILY SERVINGS OF VEGETABLES AND FRUIT
FROM EACH BOTANICAL FAMILY
Cruciferae
Rutaceae
5 Family – Cruciferae – Chenopodiaceae – Liliaceae – Rutaceae – Solanaceae
17 Family – Chenopodiaceae
Ericaceae – Cruciferae
Graminae – Liliaceae
Leguminosae – Rutaceae
Musaceae – Solanaceae
Rosaceae – Actinidiaceae
Umbelliferae – Agaricaceae
Vitaceae – Compositae
Curcurbitaceae – Convolvulaceae
Possible Explanations
•Plant foods don’t have any effect on the development of
chronic diseases like cancer.
•The way humankind eats plant foods doesn’t have any
effect on the development of chronic diseases like cancer.
•The way scientists measure plant food consumption is
insufficient to detect true effects on health that exist.
Crops for Health
•Plant food consumption (VF) is insufficient.
•Human eating patterns lack sufficient botanical diversity to
promote health/prevent disease.
•Insufficient emphasis on Staple Food Crops vs VF
•Varieties (cultivars) within a food crop differ markedly in
protective activity.
VEGETABLES AND FRUIT A Good Drug Delivery Vehicle for CDP?
• How consistent is your consumption of
vegetables and fruit?
• Do you consume 5-9 or more servings per
day of vegetables and fruit?
FOOD IS THE VEHICLE OF CHOICE
FOR THE DELIVERY OF HEALTH
PROMOTING CHEMICALS
SAFE, HIGH EFFICACY AND TASTY!
Rethink Staple Food Crops
Legumes:
• Pulses (grain): dry beans, dry peas, lentils, chickpeas
• Oil seeds: soybean, peanut
Agricultural Sciences
Consumer
Grocer
A Transdisciplinary Approach to
Chronic Disease Prevention
Biomedical Sciences Lab
Farmer
Biomedical Agriculture
Crops for Health
Different approaches/innovative solutions
Vision
Provide consumers in the global market place
with human health optimized crop varieties
and a practical framework for their use
Global Biodiversity
NOT
Genetic
Engineering
Do dry beans have an effect
on experimentally induced
breast cancer?
Are all beans created equal?
Pre-Clinical Model for Breast Cancer
Carcinogen
Injected
Intervention
Study
Terminated IDP DCIS
& AC
• The disease is Carcinogenesis
NOT Cancer
– A process
– Multiple obligatory steps
•Milled
•Freeze dried (Van Drunen Farms)
•Incorporated into purified diet (CSU)
•Cooked, canned (Bush Bros)
•Identity preserved seed (ADM)
Dose Incidence
%
Multiplicity AC/rat
Tumor Burden
g/rat
Control 70
3.13 1.85
7.5% Bean 57
2.17 1.43
30% Bean 57
1.73 0.86
60% Bean 41
1.48 0.67
plinear trend 0.045 0.0003 0.01
Treatment(no. of rats) Mammary Cancer Incidence
(%) AC/rat
(mean±SE)
1 Control (n=36) 81 1.72±0.22 2 Tamoxifen 50 µg/kg (n=39) 64 1.23±0.21
3 Tamoxifen 100 µg/kg (n=39) 59 0.95±0.17†
Inca
Middle American
Durango
Pinto
Great Northern
Small Red
Pink
Jalisco
Flora de Mayo
Flora de Juneo
Mesoamerica
Black
Navy
Small White
Andean
Peruvian
Nuna Bean
Chilean Nueva
Grenada
Light Red Kidney
Dark Red Kidney
White Kidney
Cranberry Crop Sci. 2009. 49:179–186
Obesity
Heart
Disease
Diabetes:
Type-2
Cancer
Altered glucose
utilization
Cellular
oxidation Inflammation
•Underlying Pathogenesis
Metabolic Alterations Underlying the Pathogenesis of
Chronic Diseases
Cell Proliferation
Vascularity Cell Death
One Crop as food, Many Targets
QTL
Cell Proliferation
Vascularity Cell Death
Altered glucose
utilization
Cellular
oxidation
Inflammation
050-200
200-300
300-400
400-500
500-600
600-700
700-800
800-900
900-1500
0
10
20
30
40
50
60
70
80
90
100
# o
f m
eta
bo
lite
s
Metabolite mass
White Kidney
Navy
Small Red
Mass Possible cmpd classes
50-200 NPAA’s, amines
200-300 Flavonoids, sesquiterpenes, phenylpropanoids, alkaloids
300-400 Flavonoids, alkaloids
400-500 Triterpenes, steroids, saponins, alkaloids
500-600 Tetraterpenes, alkaloids
600-700 Alkaloids
700-800 Alkaloids
800-900 Alkaloids, phopholipids
900-1500 Phopholipids
Bean Diets: How do they affect chemical profiles within the body?
Diet
MG Tumor
Plasma
Carbon Fixation
Carbohydrates
• Sugar Monosaccharides
• Disaccharides
• Oligosaccharides
• Polysaccharides
• Sugar Alcohols
Secondary
metabolites
No. of
chemicals
Alkaloids 12,000
Triterpenes,
Saponins Steroids
4000
Sesquiterpenes 3000
Diterpenes 2000
Flavonoids 2000
Polyacetylenes 1000
Phenylpropanes 1000
Monoterpenes 1000
Polyketides 750
Non-protein amino
acids
600
Tetraterpenes 350
Cyanogenic
glycosides
100
Glucosinolates 100
Amines 70
Mitchell et al. JADA 2009
•0.1 serving/d
•Only 7.9% of
Americans on any given
day
AN UNRECOGNIZED
PUBLIC HEALTH
OPPORTUNITY
Barriers Research
•Bean Awareness
•Bean know-how
•Bean myths
The Beaning of America!
Wheat
PCA of metabolomic analysis 50 wheat cultivars
Durum
Soft
Hard
-2
-1
0
1
2
3
4
5
Ave. T
um
or
Mass/r
at, g
Trait Definition Experiments
Longevity Extension
Unlocking the Commodity Market
Potato Breeding Program
IR6
4
IAC
165
M202
Mo
rob
erk
an
Do
m S
ufi
d
Cyp
ress
Po
kkali
Asw
ina
Sw
arn
a
Inia
To
cu
ari
Co 39 Patbyeo Gerdeh Dular Sadu-cho
Panicle/Seed Types in Current SNP set
Trait Definition Experiments
LLongevity Extension
Rethinking corn as a contemporary
staple: what are its health benefits?
Food versus ingredients???
40.0
42.0
44.0
46.0
48.0
50.0
52.0
54.01
0/2
0/2
00
9
10
/23
/20
09
10
/26
/20
09
10
/28
/20
09
10
/30
/20
09
11
/2/2
00
9
11
/4/2
00
9
11
/6/2
00
9
11
/9/2
00
9
11
/11
/20
09
11
/13
/20
09
11
/16
/20
09
11
/18
/20
09
11
/20
/20
09
11
/23
/20
09
11
/25
/20
09
11
/27
/20
09
11
/30
/20
09
12
/2/2
00
9
12
/4/2
00
9
12
/7/2
00
9
12
/9/2
00
9
168 171 174 176 178 181 183 185 188 190 192 195 197 199 202 204 206 209 211 213 216 218
0 3 6 8 10 13 15 17 20 22 24 27 29 31 34 36 38 41 43 45 48 50
Bo
dy
We
igh
t (g
)
Date/DOA
CSU-074 Body Weights
1 - HIGH FAT
2 - IR64 RICE
3 - NAVY BEAN
4 - SMALL RED BEAN
5 - WHITE KIDNEY BEAN
6 - RED FLESH POTATO
7 - BREAD
8 - YACON
9 - PURPLE POTATO
10 - LOW FAT
11 - BLACK RICE
12 - MAHOGANY RICE
Primary origin center
Better Food, Every Person, Every
Day, The World Round Healthy food, Healthy living: natural, affordable, delicious, nutritious
Our Friends: Our Ambassadors
We have a dream!
SAVE A MILLION LIVES
(Through Chronic Disease Prevention)
YES WE CAN!
• Drink 1% milk*
• Maintain a Body Mass Index (BMI):22-23
• Eat beans every day (0.5-1.5 C cooked bean/d)
• Eat staple food pairs every meal (cereal:pulse grains, 2:1)
• Eat the whole food…(eliminate one ingredient food/week)
• 5-9 Fruits & Vegetables/day_2:1 Vegetables:Fruits
• Eat the whole botanical tree: target branch count-18/day
• Total daily beverage count >50% water
• Sleep 7-8 hrs/day; sit fewer hours per day than you sleep
• Routinely walk 10,000 steps per day
Henry’s top 10 guesses (eat healthy/live healthy)
*Heath, C. & Heath, D.
(2010). Switch: How to
change things when
change is hard. New
York: Broadway Books.
Obesity Trends* Among U.S. Adults
BRFSS, 1985 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)
No Data <10% 10%–14%
Obesity Trends* Among U.S. Adults
BRFSS, 1986 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)
No Data <10% 10%–14%
Obesity Trends* Among U.S. Adults
BRFSS, 1987 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)
No Data <10% 10%–14%
Obesity Trends* Among U.S. Adults
BRFSS, 1988 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)
No Data <10% 10%–14%
Obesity Trends* Among U.S. Adults
BRFSS, 1989 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)
No Data <10% 10%–14%
Obesity Trends* Among U.S. Adults
BRFSS, 1990 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)
No Data <10% 10%–14%
Obesity Trends* Among U.S. Adults
BRFSS, 1991 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)
No Data <10% 10%–14% 15%–19%
Obesity Trends* Among U.S. Adults
BRFSS, 1992 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)
No Data <10% 10%–14% 15%–19%
Obesity Trends* Among U.S. Adults
BRFSS, 1993 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)
No Data <10% 10%–14% 15%–19%
Obesity Trends* Among U.S. Adults
BRFSS, 1994 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)
No Data <10% 10%–14% 15%–19%
Obesity Trends* Among U.S. Adults
BRFSS, 1995 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)
No Data <10% 10%–14% 15%–19%
Obesity Trends* Among U.S. Adults
BRFSS, 1996 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)
No Data <10% 10%–14% 15%–19%
Obesity Trends* Among U.S. Adults
BRFSS, 1997 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)
No Data <10% 10%–14% 15%–19% ≥20%
Obesity Trends* Among U.S. Adults
BRFSS, 1998 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)
No Data <10% 10%–14% 15%–19% ≥20%
Obesity Trends* Among U.S. Adults
BRFSS, 1999 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)
No Data <10% 10%–14% 15%–19% ≥20%
Obesity Trends* Among U.S. Adults
BRFSS, 2000 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)
No Data <10% 10%–14% 15%–19% ≥20%
Obesity Trends* Among U.S. Adults
BRFSS, 2001 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)
No Data <10% 10%–14% 15%–19% 20%–24% ≥25%
(*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)
Obesity Trends* Among U.S. Adults
BRFSS, 2002
No Data <10% 10%–14% 15%–19% 20%–24% ≥25%
Obesity Trends* Among U.S. Adults
BRFSS, 2003 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)
No Data <10% 10%–14% 15%–19% 20%–24% ≥25%
Obesity Trends* Among U.S. Adults
BRFSS, 2004 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)
No Data <10% 10%–14% 15%–19% 20%–24% ≥25%
Obesity Trends* Among U.S. Adults
BRFSS, 2005 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)
No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%
Obesity Trends* Among U.S. Adults
BRFSS, 2006 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)
No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%
Obesity Trends* Among U.S. Adults
BRFSS, 2007 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)
No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%
BODY WEIGHT IN POUNDS ACCORDING TO HEIGHT AND BODY MASS INDEX
Each entry gives the body weight in pounds (lbs.) for a person of a given height and body mass index. Pounds
have been rounded off. To use the table, find the appropriate height in the left hand column. Move across the
row to a given weight. The number at the top of the column is the body mass index for the height and weight.
BMI = 705 x Body Weight (in pounds) divided by [Height x Height (in inches)]
19 20 21 22 23 24 25 26 27 28 29 30 35 40
Ht. (in.)
58 91 96 100 105 110 115 119 124 129 134 138 143 167 191
59 94 99 104 109 114 119 124 128 133 138 143 148 173 198
60 97 102 107 112 118 123 128 133 138 143 148 153 179 204
61 100 106 111 116 122 127 132 137 143 148 153 158 185 211
62 104 109 115 120 126 131 136 142 147 153 158 164 191 218
63 107 113 118 124 130 135 141 146 152 158 163 169 197 225
64 110 116 122 128 134 140 145 151 157 163 169 174 204 232
65 114 120 126 132 138 144 150 156 162 168 174 180 210 240
66 118 124 130 136 142 148 155 161 167 173 179 186 216 247
67 121 127 134 140 146 153 159 166 172 178 185 191 223 255
68 125 131 138 144 151 158 164 171 177 184 190 197 230 262
69 128 135 142 149 155 162 169 176 182 189 196 203 236 270
70 133 139 146 153 160 167 174 181 188 195 202 207 243 278
71 136 143 150 157 165 172 179 186 193 200 208 215 250 286
72 140 147 154 162 169 177 184 191 199 206 213 221 258 294
73 144 151 159 166 174 182 189 197 204 212 219 227 265 302
74 148 155 163 171 179 186 194 202 210 218 225 233 272 311
75 152 160 168 176 184 192 200 208 216 224 232 240 279 319
76 156 164 172 180 189 197 205 213 221 230 238 246 287 328
Body Mass Index (kg/m2)
Body Weight (lbs.)
MARKETING DOLLARS
Oils Fats Sweets
Veg. Fruit
Grains
Dairy Meats
Crops for Health Discovery Team • Preclinical/Field
– Liz Neil
– Barry Ogg
– Denise Rush
– Amanda Blasingame
– Angie Neil
• Molecular Biology
– Erica Danielle
– Vanessa Fizgerald
– Sophie Herrmann
– Weiqin Jiang
– Zongjian Zhu
• Clincal
– Elizabeth Daeninck
– Sara Bartels
– Mary Playdon
– Lara Ulfers
– Scot Sedlacek
• Pathology
– John McGinley
– Audrey Barnett
– Joy Hester
– Jen Price
– Leslie Brick
– Laura Hester
– Meenakshi Singh
• Chemistry/Biochemistry
– Matthew Thompson
– Meghan Mensack
– Sung Gu Lee
– Erica McDaniell
– Meena Santra
• Graduate Students
– Adam Heuberger
– Tatiana Zuber
– Shawna Matthews
• Faculty
– Mark Brick
– Patrick Byrne
– Scott Haley
– Gary Peterson
– David Holm
– Cecil Stushnoff
– Jorge Vivanco
– Steve Wallner
– Jan Leach
– Daniel Bush
– A. Reddy
– Christopher Melby
– Michael Pagliosotti
– Elizabeth Ryan
– Barbara Wallner
– Lorann Stallones
– Jairam Vanamala
– Tiffany Weir
– Lavanya Reddivari
Biomedical Agriculture
Underfed
Adequate/
Overfed
Chronic
Diseases (>60% death)
Malnutrition
Biofortification
T
T
Crop Improvement for
Human Health
Related Documents
