Skip Navigation



Journal of Heredity Advance Access published online on December 8, 2006
Journal of Heredity, doi:10.1093/jhered/esl041
This Article
Right arrow Abstract Freely available
Right arrow FREE Full Text (PDF) Freely available
Right arrow All Versions of this Article:
97/6/549    most recent
esl041v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Lawler, D. F.
Right arrow Articles by Lark, K. G.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Lawler, D. F.
Right arrow Articles by Lark, K. G.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© The American Genetic Association. 2006. All rights reserved. For permissions, please email: journals.permissions@oxfordjournals.org.

Heritable Components of Feline Hematology, Clinical Chemistry, and Acid–Base Profiles

Dennis F. Lawler, Kevin Chase, Robert Teckenbrock, and Karl G. Lark

From the Nutrition Research Center, Nestle Purina Company, Checkerboard Square, St Louis, MO 63164 (Lawler); Information Technology Group, Nestle Purina Company, Checkerboard Square, St Louis, MO 63164 (Teckenbrock); and Department of Biology, University of Utah, Salt Lake City, UT 84112 (Chase and Lark)

Address correspondence to D. F. Lawler at the address above, or e-mail: dennis.lawler{at}rdmo.nestle.com.

Four erythrocyte variables (erythrocyte count, hemoglobin, mean cell volume, packed cell volume), 14 serum variables (alanine transferase, albumin, alkaline phosphatase, calcium, chloride, cholesterol, creatinine, glucose, phosphorus, potassium, sodium, total protein, triglycerides, urea nitrogen), and 7 venous acid–base variables (base excess, bicarbonate, carbon dioxide partial pressure, oxygen partial pressure, oxygen saturation, pH, and total carbon dioxide) were evaluated for heritability in domestic cats (Felis catus). Values used for individual cats were expressed as the mean over all lifetime measurements, using 444–530 animals for clinical chemistry, 629 animals for acid–base, and 564 animals for erythrocyte metrics. Gender and age at death (where applicable) also were evaluated for correlation with variables. Heritabilities for clinical chemistry, acid–base, and erythrocyte variables ranged, respectively, from 0.13 to 0.78, from 0.23 to 0.59, and from 0.41 to 0.69 (P < 0.05). This result indicates that serum variability has a genetic basis and is segregating in this feline population. These findings may have important implications in both research and clinical medicine.

Hematology, clinical chemistry, and blood gas screening are used to support health maintenance programs and disease diagnosis in many species. Routine use of these variables in the clinical environment involves a synthesis with medical history, results of physical examination, and results of other diagnostic tests. Specific results often must be evaluated together because interpretation of one variable can depend on the outcomes of tests for other variables. These tests also are important components of studies that evaluate safety and efficacy of drugs and other compounds.

Important factors that lead to variability in expression of these measures among species include anatomy and function (ruminant vs. monogastric), dietary habits (herbivore, omnivore, carnivore), or species-associated behaviors. Among individuals of the same species, many physiological and environmental influences on these same variables also can be identified, including stress, obesity, pregnancy, growth, meal times and frequency, circadian fluctuations, and many diseases (Kaneko 1980). Thus, it can be appreciated that homeostasis as measured by these variables is largely circumstantial.

Several studies also have indicated a genetic basis for variability within a species (Havlik et al. 1977; Hamsten et al. 1986; Kalousdian et al. 1987; Randi and Ragni 1991; Boerwinkle et al. 1992; Heller et al. 1993; Snieder et al. 1999; Hunter et al. 2002; Bathum et al. 2004; Greenfield et al. 2004). Interesting comparative summaries of these works have appeared in some later reports (Kalousdian et al. 1987; Heller et al. 1993; Snieder et al. 1999), documenting quantitative genetic control over expression of some of these variables in plasma, serum, or urine. Among humans, these studies often have used twins to segregate environmental and genetic influences by comparing monozygotic and dizygotic pairs (Kalousdian et al. 1987). In addition, it is becoming important to understand the degree to which heritability comparisons within populations and among species can or should be generalized. Phenotypes with similar heritabilities can have very different implications in different populations or species, raising questions about potentially important gene–gene and/or gene–environment interactions.

The Purina cat population is a large colony of more than 11 000 loosely related individuals maintained under a consistent environmental and health care system over about 3 decades at a single site to conduct nutritional research. Using data from this colony, we undertook evaluation of a feline model to define the extent of genetic regulation of intraspecies variation in blood and serum expression of selected clinical measures. Our data provide quantitative heritability measurements for the erythrocyte, clinical biochemistry, and acid–base variables examined.


   Materials and Methods
Top
 Materials and Methods
Results
 Discussion
 References
 
A feline breeding and adult colony numbering an average of about 900 adult domestic shorthair cats (Felis catus) was maintained over about 3 decades at a single site to conduct nutritional research (Nestle [Ralston] Purina Company, Gray Summit, MO). Birth dates within this population range over the years 1960–2000, with about 2500 cats born after 1990. In each generation, many cats were retained in the colony while some new cats were introduced in order to avoid the problems that accompany inbreeding. The deepest pedigree is 14 generations. This population represents a diverse genetic background with a wide range of consanguinities (f = 0.0–0.33), resulting in a wide range of phenotypes with enough relatives to provide power for genetic analysis.

Erythrocyte variables, clinical chemistry, and acid–base profiles are part of the nutritional database maintained on this population. A group of these variables were extracted for genetic analysis: 1) erythrocytes as erythrocyte count, hemoglobin, mean cell volume, and packed cell volume; 2) serum biochemistry as alanine transferase, albumin, alkaline phosphatase, calcium, chloride, cholesterol, creatinine, glucose, phosphorus, potassium, sodium, total protein, triglycerides, and urea nitrogen, and 3) venous acid–base metrics as base excess, bicarbonate, carbon dioxide partial pressure, oxygen partial pressure, oxygen saturation, pH, and total carbon dioxide. In order to increase the robustness of these estimates, likely nonphysiological values were removed, positively skewed nonnormal traits were log transformed to obtain a more normal distribution, and subsets of the data were used for which each subject was measured three or more times. Nonphysiological values were defined as those magnitudes that could not result from normal or abnormal physiological states. The "shapiro.test" of R (R Development Core Team 2005) was used to test for normal distributions of traits.

The "polygenic" function of SOLAR was used to estimate heritabilities as the ratio of additive genetic variance to total variance (Almasy and Blangero 1998). This program estimates the additive genetic variance by relating the additive genetic relationship matrix (e.g., twice the coefficient of coancestry between pairs of individuals) to the phenotypic covariance. Because the data were archived from a nutrition research facility, multiple regression techniques were used to adjust for diet within study, where applicable:

Formula
where y is the trait of interest, c is the cat identification, d is the diet, s is gender, and e is the error. The coefficients for each cat from this multiple regression were used for subsequent heritability analysis. Coefficients for each trait were also tested for correlations with age at death and gender using the Pearson correlation coefficient (Press et al. 1988).


   Results
Top
 Materials and Methods
 Results
Discussion
 References
 
Summary data for erythrocytes, clinical chemistry, and blood gas variables are listed. (Tables 1–3) For each variable, the heritability with its standard error is shown, together with the population mean and the range of values (minimum and maximum), the number of animals analyzed, and correlations with gender and age at death. Even with standardized sampling conditions (fasted baseline samples drawn in the morning using the same methods), a wide range of individual values were encountered, much of which could be explained as heritable variation.


View this table:
[in this window]
[in a new window]

  		Table 1. Heritability of hematology variables among 564 adult cats

 
Erythroctyes
All 4 erythrocyte variables were significantly (P < 0.05) heritable, and low correlations (P < 0.05) to gender were found for all 4 variables. Erythrocyte count, hemoglobin, and packed cell volume correlated positively with female gender, whereas mean cell volume correlated positively with male gender. Mean cell volume had low positive correlation (P < 0.05) with age at death, whereas erythrocyte count and hemoglobin had low negative correlation (P < 0.05) with age at death (Table 1).

Clinical Chemistry
All 14 clinical chemistry variables were significantly (P < 0.05) heritable, and low correlations (P < 0.05) with gender, of mixed male–female rank, were found for 10 of the variables. Only serum calcium, glucose, phosphorus, and urea nitrogen were independent of gender. Low correlations (P < 0.05) with age at death were found for alanine transferase, chloride, glucose, potassium, sodium, and total protein; correlations were negative for potassium and sodium (Table 2).


View this table:
[in this window]
[in a new window]

  		Table 2. Heritability of clinical chemistry variables among 444–530 adult cats

 
Acid–Base Metrics
All 7 venous variables were significantly (P < 0.05) heritable. Low correlations (P < 0.05) with gender were found for all variables except oxygen saturation. Males had generally higher values for gender correlations. Low negative correlations (P < 0.05) with age at death were found for all variables except pO2 (Table 3).


View this table:
[in this window]
[in a new window]

  		Table 3. Heritability of blood gas variables among 629 adult cats

 

   Discussion
Top
 Materials and Methods
 Results
 Discussion
References
 
As in other mammals, erythrocyte, clinical chemistry, and acid–base profiles in cats are mostly heritable, implying a substantial degree of genetic variability. These profiles are designed as screening panels to reflect organ or metabolic dysfunction. The underlying principle is individual expression relative to a reference interval that separates "normal" from "abnormal." Despite their origin and uses, many of these blood and serum variables can be relatively insensitive to covert changes until more serious or extensive damage has occurred. In addition, individual variation within reference intervals can at times denote pathological change, whereas individual variation outside of reference intervals can at times still reflect normality.

There exist also a number of well-known procedural challenges and caveats in the interpretation of these data. Reference intervals for each variable typically are established at each laboratory and usually are based on analytical survey of "clinically healthy" subjects (Ash 1980). Potential problems with this practice include 1) some outwardly normal individuals may harbor covert abnormalities; 2) the statistical structure of reference intervals can be based on percentiles, quartiles, standard deviations, or occasionally the lowest-to-highest data range within the sampled population, making comparative evaluations among laboratories more difficult; and 3) some variables do not exhibit Gaussian distribution, which must be considered during interpretation. It is readily apparent that a degree of deviation from reference is inevitable in routine metabolic profiling (Ash 1980; Wilkins and Hurvitz 1980; Rebar and Boon 1983).

Based on current technology, the most appropriate means of providing contiguity in health care is annual individual screening for baseline reference. In population studies, including biomedical research, it is important to realize that pooled data from different laboratories potentially introduce biases resulting from differing sampling conditions, analytical methods, equipment, and reference intervals. Therefore, even when optimal genetic controls exist, such as comparing data from monozygotic and dizygotic twins, other biases remain and need to be considered.

Given the numerous procedural and analytical difficulties that are known to exist in clinical chemistry, robustness is suggested by the relative consistency among heritability studies of these variables, across populations, within species, and across species. Nonetheless, physiological implications of the phenotypic expressions of variables with similar heritabilities among species may be very different. Several important examples may be considered.

Alkaline Phosphatase
Serum alkaline phosphatase expression was highly heritable (0.78) in our cat database. Alkaline phosphatases are a group of membrane-bound glycoproteins that are present in the body as multiple isoenzymes. Tissue expression of specific isoenzymes appears to result from posttranslational modification (Siraganian et al. 1989). Multiple isoenzymes in serum most probably reflect clearance from tissues (Kruse 1983; Siraganian et al. 1989). Distribution of alkaline phosphatase in reference populations typically is non-Gaussian, and there are gender and age effects (Lewis 1987). It has been reported that feline liver/bone/kidney alkaline phosphatase is 88–90% homologous to other mammals (Ghosh and Mullins 1995). Separate loci code for human liver/bone/kidney, placental, and intestinal isoenzyme. Placental/intestinal isoenzymes are homologous and located on chromosome 2, whereas the liver/bone/kidney isoenzyme locus, common to both mouse and humans, is located on human chromosome 1 (Ghosh and Mullins 1995).

Evaluations of different human test groups yielded alkaline phosphatase heritability ranging between 0.00 and 0.81 (Havlik et al. 1977; Colletto et al. 1981; Whitfield and Martin 1983, 1984; Kalousdian et al. 1987) and included different metholodology-associated outcomes within the same study (Kalousdian et al. 1987), thus emphasizing the importance of considering influences of data collection procedures. In humans and Siberian Husky dogs, extreme but benign overexpression of serum alkaline phosphatase has been described as a presumed recessive trait (Iancu et al. 1978; Dunn et al. 1979; Wilson 1979; Kruse 1983; Siraganian et al. 1989; Panteghini 1991; Lawler et al. 1996) that has not been reported in cats or other mammalian species. It has been recognized for many years that alkaline phosphatase expression in cat serum tends to be substantially lower than in dogs and humans, even during pathological states (Everett et al. 1977; McLain et al. 1978; Horney et al. 1992). Thus, smaller changes in serum expression of alkaline phosphatase in cats must be interpreted as having much greater physiological significance, compared with other species.

Glucose
The exaggerated hyperglycemic response of domestic cats to short-term stress has been recognized for many years (Kaneko 1980; Thibault and Roberge 1988). Momentary excitement in a sampling room, which is very common in cats, and short-term effects of unfamiliar cage confinement, both are sufficient to produce dramatically increased circulating glucose in cats (Thibault and Roberge 1988). In our study of cats, heritability of serum glucose expression was moderate (0.39) in a well-controlled environment. In one study of Finnish human twins, heritability of fasting glucose expression was only slightly greater, at 0.45 (Katoh et al. 2005). A study of fasting plasma glucose also was done with Brazilian twins, with heritability of glucose expression reported as 0.73 (Colletto et al. 1981). In post–glucose loading measurements conducted with twins at 5 American centers, heritability of plasma glucose expression postloading was 0.88 in a first examination and 0.52 in a second examination (Kalousdian et al. 1987).

It is interesting that the cat population had lower heritability for fasted serum glucose expression than several human twin populations, but the human populations also revealed widely differing within-species results. These observations suggest again that study design and data collection procedures are very important considerations for the outcomes of heritability studies within populations, even if these populations are selected and structured to favor rigorous procedures. In addition, it is understood widely by veterinary clinicians that interpretation of elevated serum fasted glucose expression in domestic cats depends substantially on physiological status and the immediate environment at the time of sampling. Thus, results of serum glucose determinations in cats are subject to a somewhat different range of possible interpretations than are the same results in humans.

Creatinine
Serum creatinine expression is a function of spontaneous breakdown of skeletal muscle. Creatinine production is constant, resulting from unidirectional nonenzymatic dehydration of skeletal muscle creatine (First 2003). Elevations of serum creatinine most frequently are associated with renal compromise but can be associated also with changes such as state of hydration or declining lean body composition. Because many of the changes in serum creatinine occur during advanced life, it is useful but also potentially confusing to consider heritability evaluations of older subjects. In a study of elderly Danish twins (Bathum et al. 2004), elevated values predicted shorter overall survival, as expected, and heritability of serum creatinine expression ranged from 0.00 in men to 0.44 in women. In another large study of British twins between ages 18 and 72 years, heritability of serum creatinine expression was 0.37 (Hunter et al. 2002). Serum creatinine heritability was 0.25 in our study of cats, which included all adult ages and both genders, and there was no correlation to age at death.

Among mammalian species, serum creatinine has a non-Gaussian distribution, tends to occur over a relatively narrow numerical range among healthy individuals, and tends to be interpreted similarly among species. Thus, the comparative data might suggest that the environmental component in cats might be of somewhat greater importance than the environmental component in humans. However, such an interpretation would need to be taken very cautiously because of variation in the heritability results among human populations. These differences suggest that the human populations that were selected and evaluated likely were subject to differing demographic influences, whereas our cats all were maintained for life under uniform environmental conditions. It is interesting in this respect that results of a study of young adult twins suggested that fetoplacental factors were more important to expression of serum creatinine than were genetic and maternal factors alone (Gielen et al. 2005).

Cholesterol and Triglyceride
A final important example is the large difference in heritability between the serum lipid fractions total triglyceride (0.13) and total cholesterol (0.47) in cats. It has been shown in diet restriction trials across species that circulating total cholesterol is less influenced than is circulating total triglyceride (Liepa et al. 1980; Masoro et al. 1983; Choi et al. 1988; Van Liew et al. 1993; Bodkin and Hansen 1995; Cefalu et al. 1997; Verdery et al. 1997; Edwards et al. 1998; Lane et al. 1998; Kealy et al. 2002), suggesting that expression of serum cholesterol might be less subject to environmental influence than serum triglyceride.

Plasma lipids are known to change significantly with age (Greenfield et al. 2004), although cross-sectional heritability studies usually do not evaluate longitudinal changes (Snieder et al. 1999). Genetic and environmental effects may exert influence at different ages, either due to changing magnitude of the effect or to age-related changes in gene expression (Snieder et al. 1999). In most studies of humans, more than 50% of the variation in serum total cholesterol and triglyceride is genetically mediated (Snieder et al. 1999), which is compatible with our findings for expression of serum cholesterol but not triglyceride in cats.

There exists significant species difference between cats and humans with respect to implications of levels of serum lipid expression. Despite the relatively high heritability of serum cholesterol expression in cats (0.47) and humans (0.35–0.72, summarized by Heller et al. 1993), cardiovascular disease secondary to athersosclerosis is a very common complication of chronic hypercholesterolemia in humans but has not been reported in cats (Fox et al. 2005). On the other hand, hepatic lipidosis and associated hepatic failure in cats is a well-known and serious complication of dysfunctional triglyceride metabolism that seems to occur uniquely in cats (Scherk and Center 2005).

The foregoing comparative examples suggest that epidemiological factors that operate within and among specific populations can have substantial impact on outcomes of heritability studies. Therefore, comparing species heritabilities needs to be approached very cautiously. Our population, from which these data were derived, was maintained in a stable and healthy state over nearly 4 decades for the purpose of conducting nutritional research. Better populations might be structured for specific genetic purposes, and our results may be used as a guide for design and interpretation of future experiments.


   Footnotes
 
Corresponding Editor: Stephen J. O'Brien

Received February 27, 2006
Accepted September 21, 2006


   References
Top
 Materials and Methods
 Results
 Discussion
 References
 

    Almasy L and Blangero J. (1998) Multipoint quantitative trait linage analysis in general pedigrees. Am J Hum Genet 62:1198–1211.[CrossRef][Web of Science][Medline]

    Ash KO. (1980) Reference intervals (normal ranges): a challenge to laboratorians. Am J Med Technol 46:504–511.[Web of Science][Medline]

    Bathum L, Fagnani C, Christiansen L, Christensen K. (2004) Heritability of biochemical kidney markers and relation to survival in the elderly—results from a Danish population-based twin study. Clin Chim Acta 349:143–150.[CrossRef][Web of Science][Medline]

    Bodkin NL and Hansen BC. (1995) Prevention of Syndrome X by long-term dietary restriction (DR) in aged rhesus monkeys. Gerontologist 35:239.

    Boerwinkle E, Leffert CC, Lin J, Lackner C, Chiesa G, Hobbs HH. (1992) Apolipoprotein (a) gene accounts for greater than 90% of the variation in plasma lipoprotein (a) concentrations. J Clin Investig 90:52–60.[Web of Science][Medline]

    Cefalu WT, Wagner JD, Zhong QW, Bell-Farrow AD, Collins J, Haskell D, Bechtold R, Morgan T. (1997) A study of caloric restriction and cardiovascular aging in cynomolgus monkeys (Macaca fascicularis): a potential model for aging research. J Gerontol A Biol Sci Med Sci 52:B10–B19.[Abstract]

    Choi Y-S, Goto S, Ikeda I, Sugano M. (1988) Age-related changes in lipid metabolism. Biochem Biophys Acta 963:237–242.[Medline]

    Colletto GMDD, Krieger H, Magalhaes JR. (1981) Estimates of the genetical and environmental determinants of serum lipid and lipoprotein concentrations in Brazilian twins. Hum Hered 31:232–237.[CrossRef][Web of Science][Medline]

    Dunn V, Condon V, Rallison M. (1979) Familial hyperphosphatasemia: diagnosis in early infancy and response to human thyrocalcitonin therapy. Am J Radiol 32:541–545.

    Edwards IJ, Rudel LL, Terry JG, Kemnitz JW, Weindruch R, Cefalu WT. (1998) Caloric restriction in rhesus monkeys reduces low density lipoprotein interaction with arterial proteoglycans. J Gerontol A Biol Sci Med Sci 53:B443–B448.[Abstract]

    Everett RM, Duncan JR, Prasse KW. (1977) Alkaline phosphatase, leucine aminopeptidase, and alanine aminotransferase activities with obstructive and toxic hepatic disease in cats. Am J Vet Res 38:963–966.[Web of Science][Medline]

    First MR. (2003) Renal function. In Kaplan LA, Pesce AJ, Kazmierczak SC (Eds.). Clinical chemistry: theory, analysis, correlation 4th ed. (Mosby, St. Louis (MO)) pp. 483–484.

    Fox PR, Petrie JP, Hohenhaus AS. (2005) Peripheral vascular disease. In Ettinger SJ and Feldman EC (Eds.). Textbook of veterinary internal medicine 6th ed. (WB Saunders, Philadelphia (PA)) Vol. 2: pp. 1156.

    Ghosh AK and Mullins JI. (1995) cDNA encoding a functional feline liver/bone/kidney-type alkaline phosphatase. Arch Biochem Biophys 322:240–249.[CrossRef][Web of Science][Medline]

    Gielen M, Pinto-Sietsma S-J, Zeegers MP, Loos RJ, Fagard R, deLeeuw PW, Beunen G, Derom C, Vlietinck R. (2005) Birth weight and creatinine clearance in young adult twins: influence of genetic, prenatal, and maternal factors. J Am Soc Nephrol 16:2471–2476.[Abstract/Free Full Text]

    Greenfield JR, Samaras K, Jenkins AB, Kelly PJ, Spector TD, Campbell LV. (2004) Do gene-environment interactions influence fasting plasma lipids? A study of twins. Eur J Clin Investig 34:590–598.[CrossRef][Web of Science][Medline]

    Hamsten A, Iselius L, Dahlen G, de Faire U. (1986) Genetic and cultural inheritance of serum lipids, low and high density lipoprotein cholesterol and serum apolipoproteins A-I, A-II and B. Atherosclerosis 60:199–208.[CrossRef][Web of Science][Medline]

    Havlik R, Garrison R, Fabsitz R, Feinleib M. (1977) Genetic variability of clinical chemistry values. Clin Chem 23:659–662.[Web of Science][Medline]

    Heller DA, de Faire U, Pedersen NL, Dahlen G, McClearn GE. (1993) Genetic and environmental influences on serum lipid levels in twins. N Engl J Med 328:1150–1156.[Abstract/Free Full Text]

    Horney BS, Farmer AJ, MacKensie A, Honor DJ, Buczkowski S. (1992) Alkaline phosphatase isoenzymes in feline serum using an agarose gel alkaline phosphatase kit method. Can J Vet Res 56:373–375.[Web of Science][Medline]

    Hunter DJ, de Lange M, Snieder H, MacGregor AJ, Swaminathan R, Thakker RV, Spector TD. (2002) Genetic contribution to renal function and electrolyte balance: a twin study. Clin Sci (Lond) 103:259–265.[Medline]

    Iancu TC, Almagor G, Friedman E, Hardoff R, Front D. (1978) Chronic familial hyperphosphatasemia. Radiology 129:669–676.[Abstract]

    Kalousdian S, Fabsitz R, Havlik R, Christian J, Rosenman R. (1987) Heritability of clinical chemistries in an older twin cohort: the NHLBI Twin Study. Genet Epidemiol 4:1–11.[Medline]

    Kaneko JJ. (1980) Clinical biochemistry of domestic animals. 3rd ed (Academic Press, New York (NY)).

    Katoh S, Lehtovirta M, Kaprio J, Harjutsalo V, Koskenvuo M, Eriksson J, Tajima N, Tuomilehto J. (2005) Genetic and environmental effects on fasting and postchallenge plasma glucose and serum insulin values in Finnish twins. J Clin Endocrinol Metab 90:2642–2647.[Abstract/Free Full Text]

    Kealy RD, Lawler DF, Ballam JM, Mantz SL, Biery DN, Greeley EH, Lust G, Segre M, Smith GK, Stowe HD. (2002) Effects of diet restriction on life span and age-related changes in dogs. J Am Vet Med Assoc 220:1315–1320.[CrossRef][Web of Science][Medline]

    Kruse K. (1983) Inherited isolated hyperphosphatasemia. Acta Paediatr Scand 72:833–835.[Web of Science][Medline]

    Lane MA, Black A, Ingram DK, Roth GS. (1998) Calorie restriction in nonhuman primates: implications for age-related disease. J Anti Aging Med 1:315–326.

    Lawler DF, Keltner DG, Hoffman WE, Nachreiner RF, Hegstad RL, Herndon PA, Fischer BS. (1996) Benign familial hyperphosphatasemia in Siberian Huskies. Am J Vet Res 57:612–617.[Web of Science][Medline]

    Lewis MJ. (1987) Persistent isolated hyperphosphatasemia. South Med J 80:788–790.[CrossRef][Web of Science][Medline]

    Liepa GU, Masoro EJ, Bertrand HA, Yu BP. (1980) Food restriction as a modulator of age-related changes in serum lipids. Am J Physiol 238:E253–E257.

    Masoro EJ, Compton C, Yu BP, Bertrand H. (1983) Temporal and compositional dietary restrictions modulate age-related changes in serum lipids. J Nutr 113:880–892.[Abstract/Free Full Text]

    McLain DL, Nagode LA, Wilson GP, Kociba GL. (1978) Alkaline phosphatase and its isoenzymes in normal cats and in cats with biliary obstruction. J Am Anim Hosp Assoc 14:94–99.

    Panteghini M. (1991) Benign inherited hyperphosphatasemia of intestinal origin: report of two cases and a brief review of the literature. Clin Chem 37:1449–1452.[Abstract/Free Full Text]

    Press WH, Flannery BP, Teukolsky SA, Vettering WT. (1988) Numerical references in C. 2nd ed (Cambridge University Press, Cambridge (UK))636.

    Randi E and Ragni B. (1991) Genetic variability and biochemical systematics of domestic and wild cat populations. J Mammal 72:79–88.[CrossRef]

    R Development Core Team. (2005) A language and environment for statistical computing [Internet] [cited 2006 November]. Available from: http://www.R-project.org.

    Rebar AH and Boon GD. (1983) A case-oriented approach to small animal biochemical profiling. (Ralston Purina Company, St Louis (MO)).

    Scherk MA and Center SA. (2005) Toxic, metabolic, infectious, and neoplastic liver diseases. In Ettinger SJ and Feldman EC (Eds.). Textbook of veterinary internal medicine 6th ed. (WB Saunders, Philadelphia (PA)) Vol. 2: pp. 1471–1473.

    Siraganian PA, Mulvihill JJ, Mulivor RA, Miller RW. (1989) Benign familial hyperphosphatasemia. J Am Med Assoc 261:1310–1312.[Abstract/Free Full Text]

    Snieder H, van Doornen LJP, Boomsma DI. (1999) Dissecting the genetic architecture of lipids, lipoproteins, and apolipoproteins. Lessons from twin studies. Arterioscler Throm Vasc Biol 19:2826–2834.[Abstract/Free Full Text]

    Thibault L and Roberge AG. (1988) Dietary protein and carbohydrate effects on blood parameters related to stress in a cat. Physiol Behav 42:1–5.[CrossRef][Medline]

    Van Liew JB, Davis PJ, Davis FB, Bernardis LL, Deziel MR, Marinucci LN, Kumar D. (1993) Effects of aging, diet and sex on plasma glucose, fructosamine, and lipid concentrations in barrier-raised Fischer 344 rats. J Gerontol A Biol Sci Med Sci 48:B184–B190.

    Verdery RB, Ingram DK, Roth GS, Lane MA. (1997) Caloric restriction increases HDL2 levels in rhesus monkeys (Macaca mulatta). Am J Physiol 136:E714–E719.

    Whitfield JB and Martin NG. (1983) Determinants of variation in plasma alkaline phosphatase activity: a twin study. Am J Hum Genet 35:978–986.[Web of Science][Medline]

    Whitfield JB and Martin NG. (1984) The effects of inheritance on constituents of plasma: a twin study on some biochemical variables. Am Clin Biochem 21:176–183.

    Wilkins RJ and Hurvitz AI. (1978) Profiling in veterinary clinical pathology-dog and cat. (Technicon Instruments Corp, Tarrytown (NY)) Vol. 1:.

    Wilson JW. (1979) Inherited elevation of alkaline phosphatase activity in the absence of disease. N Engl J Med 301:983–984.[Web of Science][Medline]


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?



This Article
Right arrow Abstract Freely available
Right arrow FREE Full Text (PDF) Freely available
Right arrow All Versions of this Article:
97/6/549    most recent
esl041v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Lawler, D. F.
Right arrow Articles by Lark, K. G.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Lawler, D. F.
Right arrow Articles by Lark, K. G.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?